Build Your Own Personal Assistant with AutoGPT and ChatGPT
💡🤖 Transform Your Life with ChatGPT and Auto-GPT: Craft AI-Driven Personal Assistants, Streamline Tasks, Enhance Efficiency 🚀💼
Enroll / Gift
Are you overwhelmed with daily tasks? 😓
Struggling to stay organized and productive? 😣
Dream of having a personal assistant at your fingertips? 💭
This ChatGPT & Auto-GPT Kickstarter Bundle is the answer you've been waiting for!
If you thought ChatGPT was amazing, just wait until you see Auto-GPT.
🧠 Auto-GPT combines the intellectual power of ChatGPT with automation programming to execute tasks directly for you, hands-free.
Auto-GPT will even generate, suggest and decide which tasks to do next! 🤖
Examples of what Auto-GPT can do:
- Create and edit files
- Scrape the web for data
- Formulate a plan and execute a series of computer tasks
- Complete virtual assistant tasks
- Integrate with APIs like YouTube and Twitter to automate web tasks
Customize Auto-GPT with code or use without any special programming! It's up to you.
Pledge for a massive cutting-edge bundle
- Level 1 💬 ChatGPT Integration and Usage
- Level 2 🤖 Auto-GPT Fundamentals
- Level 3 👨💻 Build Custom Personal Assistants
- Level 4 🦾 AI-Powered Task Automation
- Level 5 ⚙️ ChatGPT & Auto-GPT Mastery and Advanced Applications
Unlock the power of AI and superboost your life with ChatGPT & Auto-GPT!
Why ChatGPT? 🗨️
ChatGPT is a highly advanced language model developed by OpenAI.
- has the power to understand and generate human-like text based on your input
- perfect for generating content and researching the web for you.
Why Auto-GPT? 💭
Auto-GPT takes ChatGPT to a whole new level.
- Cutting-edge software library
- Designed to harness the power of ChatGPT
- Simplifies the process of building personal assistants and automating tasks
- Accessible for everyone - regardless of their technical expertise
🌟 This Bundle:
- Assumes no prior experience with AI or programming 👶
- 🎓 Perfect for beginners and experts alike
- Provides step-by-step guidance and hands-on exercises
- Empowers you to build your own AI-powered solutions ✊
- 💪 Is full of practical projects
- Shows real-world business use cases 💼
- Provides all source code and prompts high-value and ready to download
Ready to embark on an exciting AI journey? Explore our 5-level curriculum!
Level 1 💬 ChatGPT Integration and Usage
- Understand the basics of ChatGPT
- Learn how to integrate ChatGPT into your applications
- Explore various use cases for ChatGPT
Start by learning the fundamentals of ChatGPT prompt engineering.
ChatGPT 4 AI Prompt Engineering for Entrepreneurs
- Build your first ChatGPT AI prompts with prompt engineering
- Automate business tasks with ChatGPT
- ChatGPT for marketing automation
- ChatGPT prompts for research, copywriting and career prep
- Automate coding with ChatGPT prompts
Connect to OpenAI's models programmatically with Python.
ChatGPT and Auto-GPT were primarily written in the Python programming language.
- Learn how to code in Python, the #1 language for finance, machine learning and data science.
- Anyone can become a coder.
- Program in the most hireable language of the decade!
Build projects with OpenAI API
- Scrape web data in text form with Python
- Process web data for OpenAI machine learning
- Customize OpenAI model to learn from your data
- Answer questions about PDF with ChatGPT model in Python
Level 2 🤖 Auto-GPT Fundamentals
- Grasp the core concepts of Auto-GPT
- Discover how Auto-GPT simplifies ChatGPT integration
- Automate tasks with Auto-GPT
- Use the command line to automate your computer
Projects you'll build:
- Run Auto-GPT with the Command Line
- Research, summarize and save with Auto-GPT
- Web development with Auto-GPT and React JS
- Automate copywriting with Auto-GPT
- Improve Auto-GPT results with plugins
- Use third party plugin in Auto-GPT
- Automate Twitter with Auto-GPT
- Write detailed image descriptions with Auto-GPT and SceneX
- Automate email with Auto-GPT
- Automate Excel files with Auto-GPT
- Web scraping with Excel and Auto-GPT
- Build web app with AI interaction in Python
- Build ChatGPT Web UI with Flask and Auto-GPT
- Style webpage with Auto-GPT and Bootstrap
Get excited!
- Get started with building your first AI-powered solutions
- Work with APIs and SDKs for seamless integration
- Learn the best practices for AI development and deployment
Level 3 👨💻 Build Custom Personal Assistants
- Design your own AI personal assistant with ChatGPT & Auto-GPT
- Customize your assistant to cater to your specific needs
- Automate finance and stock market investing
- Build custom machine learning models and chatbots
Stock analysis with ChatGPT
- Analyze financial statements of stock
- Analyze balance sheet, income statement and cash flow statement
- Identify loopholes and weaknesses in stock financials
- Analyze historical stock performance
- Predict stock performance
- Analyze market share, industry and management team
- Analyze stock risks
- Stock valuation
- Perform SWOT analysis
- Summarize a company’s earnings report calls
- Evaluate a company’s ESG credentials
Build an investment plan with ChatGPT
- Invest short term and long term
- Generate customized investment recommendations based on individual financial goals and risk tolerance
Predict stock market with ChatGPT
- Analyze past, present and future stock market state
Risk analysis of applicants with ChatGPT
- Analyze credit scores
- Assess loan applicant risk
Build a trading strategy with ChatGPT
- Pick stocks with company evaluation
- Build a trading strategy
Sentiment Analysis with ChatGPT
- Analyze news headlines in the financial sector
- Analyze social media sentiment
Fraud detection with ChatGPT
- Detect fraud in financial data
- Red flag and anomaly detection
Learn how to use popular Python libraries:
- NumPy - fundamental package for scientific computing in Python
- Matplotlib's Pyplot - data visualization with plots, graphs and charts
- Pandas - fast, powerful, flexible and easy to use data analysis and manipulation tool
Work with data using powerful Python libraries like Pandas, NumPy and MORE!
- Complete Beginners Data Analysis with Pandas and Python
- Learn to Graph Data with Python and Matplotlib
- Data Science with Python and NumPy
- Data Mining with Python! Real-Life Data Science Exercises
Learn to build AI models from scratch! No experience necessary.
- Machine Learning Theory for Business
- Machine Learning Fundamentals
- Introduction to Machine Learning and Python Data Science
Data Engineering and Machine Learning Masterclass
- Load, clean and encode data
- Build regression and discretizer models
- Data transformation and feature selection
Build Machine Learning Models and Neural Networks
- Image Recognition with MNIST dataset and Python
- AI Uninformed Search Algorithms
- Build regression and classification models with Python
Build Neural Networks with Python
- Linear algebra for deep learning
- Build convolutional neural networks for image classification
- Build a recurrent neural network
- Classify emotional sentiment of text
- Text to Speech with Python Machine Learning, Deep Learning and Neural Networks
Build beginner, intermediate and advanced chatbots with natural language processing 🤖
- Build a chatbot with NLP from a Frequently Asked Questions dataset
- Build a Context Aware chatbot with a basic generative model
- Build a chatbot with machine learning
Level 4 🦾 AI-Powered Task Automation
- Learn how to automate repetitive tasks using ChatGPT & Auto-GPT
- Streamline your workflow with AI-driven solutions
- Save time and increase productivity with automation
- Generate personalized content and recommendations
- Automate data analysis and reporting for improved decision-making
ChatGPT for Marketing Professionals
Generate Social Media with ChatGPT 4 Prompts
- Build a marketing campaign content calendar with ChatGPT
- Target audience research and assessment
- Generate social media posts
- Use SocialBee to automate social media
ChatGPT SEO blog post writing
- Generate optimized keywords
- Generate blog headlines
- Generate SEO-enhanced blog posts
Generate Emails and Ads with ChatGPT 4 Prompt Engineering
- Generate email sequences
- Generate persuasive and effective sales page copy
- Generate ads to run on Facebook, Google, Instagram and Twitter
YouTube Video Production with ChatGPT
- Generate video concepts
- Generate full video scripts
- Improve SEO strategy
Build Marketing Funnels and Analyze Customers with ChatGPT 4
- Define buyer persona
- Generate lead magnet
- Generate landing page and social media copy
- Analyze customer reviews
Web Development, Branding and eCommerce with ChatGPT 4
- Generate a simple website
- Generate product names
- Generate taglines and slogans
- Generate product descriptions for your online store
- Generate Frequently Asked Questions
Level 5 ⚙️ ChatGPT & Auto-GPT Mastery and Advanced Applications
- Dive deep into advanced ChatGPT features
- Explore innovative applications and use cases
- Master the art of AI-powered personal assistants and automation
- Leverage AI for advanced analytics and insights
- Discover the potential of AI in transforming industries
ChatGPT Prompts for Python Coders
- ChatGPT Prompts and best practices for python coders
- Import ChatGPT in Python
- Data analysis and visualization with ChatGPT and Python
- Machine learning with ChatGPT and Python
ChatGPT 4 for Web Developers - Build an eCommerce Site with JavaScript
- Build and Style a Website with ChatGPT, React, JS and CSS
- Build eCommerce Website with ChatGPT and React JS
- Build Website Shopping Cart with ChatGPT and React JS
- Web Development with ChatGPT and React JS
- Build Login Page with ChatGPT and React JS
Google Cloud Professional Machine Learning Engineer Certification Introduction
- Introduction to Cloud Computing for Machine Learning
- Image classification with AutoML and Vertex AI in Google Cloud
- Query and visualize data with BigQuery SQL
Microsoft Certified Azure Data Scientist Associate Preparation
- Build a cluster and pipeline in Azure Machine Learning
- Build a dataset in Microsoft Azure ML Studio
- Build a regression machine learning model with Azure Machine Learning
Build TensorFlow.js models for the web (20 Hours)
- Introduction to HTML
- Introduction to CSS
- Introduction to JavaScript, the #1 language for the web.
- Build Your First Tensors
- Visualize Data
- Train a Simple Model
- Generate and Visualize Data
- Build a Linear Regression Model
- Visualize Linear Regression with User Input
- Visualize Polynomial Regression with User Input
- Build a polynomial regression machine learning model
- K Nearest Neighbors Image Classification with Tensorflow JS
Use machine learning models and neural networks in websites with Tensorflow.js.
- Build Neural Network Components
- Build a Neural Network with Cross Validation
- Image Classification with a Neural Network
- Build a Neural Network for the XOR Algorithm
- Use Recurrent Neural Networks with Tensorflow JS
- Detect Objects in Images with a Neural Network
- Build a Deep Neural Network with Backpropagation
- Build a Neural Network with Gradient Descent
Build beginner to advanced projects!
- Identify Text Toxicity Scores
- Build a Speech Recognition Drawing Site
- Manage TensorFlow Memory
- Build a Housing Linear Regression Project
- Build a Model on a Large Dataset
- Build a Logistic Regression Model
- Visualize Fast Fourier Transform
- Visualize Principal Component Analysis
- Build a Neural Network with One Hot Encoding
- Build a Neural Network to Detect Lines in Images
- Build an LSTM Recurrent Neural Network
- Build a Model to Classify Iris Species
- Build a Neural Network to Recognize Handwriting
- Build a Positive vs Negative Text Classifier
Build models for mobile apps (10 Hours)
- Python and Android Tensor Flow Lite - Machine Learning for App Development
- CoreML SwiftUI Masterclass - Machine Learning App Development
Work with R (10 Hours)
- Beginners R Programming: Data Science and Machine Learning!
- R Programming: Practical Data Science and Modeling
💼 Boost Your Career and Business with AI
- Stand out in the job market with in-demand AI skills
- Improve efficiency and productivity in your business
- Create custom solutions tailored to your unique needs
- Discover new opportunities with AI-powered personal assistants and automation
- Learn from industry experts and thought leaders
🌍 Join the AI Revolution Today!
The AI market is growing at a breakneck pace, and there's never been a better time to join the revolution. With ChatGPT & Auto-GPT, you'll be at the forefront of a new industry.
AI innovation, unlocking limitless potential for your personal and professional life.
- Be part of a thriving AI community and network with like-minded individuals
- Access resources, updates, and support for continued learning and growth
- Contribute to open-source projects and collaborate on cutting-edge AI solutions
- Drive the future of AI technology and its impact on society
Lifetime Access and Ongoing Support
- Enjoy lifetime access to all course materials and updates
- Benefit from ongoing support and assistance from our expert team
- Stay ahead of the curve with the latest AI developments and breakthroughs
AI's Impact on the Global Job Market
- AI is projected to create 97 million new jobs by 2025 (source: World Economic Forum)
- 77% of companies plan to adopt AI technologies in the next 3 years (source: Gartner)
- 90% of C-level executives see AI as a game-changer for their industries (source: PwC)
Freelance and Entrepreneurial Opportunities
- Create AI-driven solutions for clients across industries
- Build your own AI-focused startup or consultancy
- Expand your existing business with AI-powered offerings
- Generate passive income with AI-based products and services
High Satisfaction and Career Growth
- AI professionals report a job satisfaction rating of 4.3 out of 5 (source: Glassdoor)
- AI specialists enjoy a high growth potential and upward mobility in their careers
- Experience the excitement of working with cutting-edge technology and driving innovation
Global Reach and Remote Opportunities
- Work from anywhere with a strong demand for AI skills in both developed and emerging markets
- Collaborate with diverse teams and contribute to AI projects worldwide
- Access remote job opportunities and freelance projects with a global clientele
Requirements
- No programming experience needed - We'll teach you everything you need to know.
- We'll walk you through, step-by-step how to get all the software installed and set up.
- Any computer with Internet access
Testimonials
Collection of reviews from various Mammoth Interactive courses.
📦 Sign up today, and look forward to:
- HD Video Lectures
- Easy to view on mobile
- Source files
- Fully Fledged Projects
- Resources and Downloads
Frequently Asked Questions
How do I obtain a certificate?
Each certificate in this bundle is only awarded after you complete every lecture of the course.
Many of our students post their Mammoth Interactive certifications on LinkedIn. Not only that, but you will have projects to show employers on top of the certification.
Is this an eBook or videos?
The majority of this bundle will be video tutorials (screencasts of practical projects step by step.) You will also get PDFs and ALL SOURCE FILES!
Can't I just learn via YouTube?
YouTube tutorials prioritize clickbait, shock factor, and hacking the recommendation algorithm. This makes it hard to find quality content.
Our online courses are completely about education. You'll be taken from absolute beginner to advanced programmer. With no ads, clickbait or shock factor.
This bundle is much more streamlined and efficient than learning via Google or YouTube. We have curated a massive curriculum to take you from zero to starting a high-paying career.
How will I practice to ensure I'm learning?
With each section there will be a project, so if you can build the project along with us you are succeeding. There is also a challenge at the end of each section that you can take on to add more features to the project and advance the project in your own time.
Your Instructor
Alexandra Kropf is Mammoth Interactive's CLO and a software developer with extensive experience in full-stack web development, app development and game development. She has helped produce courses for Mammoth Interactive since 2016, including the Coding Interview series in Java, JavaScript, C++, C#, Python and Swift.
Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard’s edX, Business Insider and more.
Over 12 years, Mammoth Interactive has built a global student community with 4 million courses sold. Mammoth Interactive has released over 350 courses and 3,500 hours of video content.
Founder and CEO John Bura has been programming since 1997 and teaching
since 2002. John has created top-selling applications for iOS, Xbox and
more. John also runs SaaS company Devonian Apps, building
efficiency-minded software for technology workers like you.
Course Curriculum
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Start00-01 Introduction Of The Instructor (2:25)
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Start01 01 What Is Chatgpt (7:50)
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Start01 02 Intro To Prompt Engineering-Prompt Types (8:28)
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Start01 03 Intro To Prompt Engineering-Effective Prompts (8:41)
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Start01B 01 Project Preview (2:04)
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Start01B 02A Simplify Complex Information (8:38)
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Start01B 02B Simplify Complex Information-Other Strategies (8:41)
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Start02 03 Proofread-Email And Business Proposals (8:39)
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Start02.03 Proofread-More Use Cases (8:24)
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Start02.04 Re-Organize Data-Benefits And First Sample Use Case (6:22)
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Start02.04 Re-Organize Data-Potential Use Cases Case (10:44)
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Start02.05 Work With Spreadsheets-Automating Data Entry (7:46)
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Start02.05 Work With Spreadsheets-Formulas And Other Use Cases (7:31)
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Start03 01 Project Preview (1:23)
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Start03.02 Create Content (4:03)
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Start03.03 Social Media (4:26)
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Start03.04 Write Ad Copy (8:17)
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Start03.05 Write Email Marketing Campaigns (4:55)
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Start03.06 Write An Outreach Message (5:08)
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Start03.07 Copyrighting (4:29)
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Start03.08 Seo (5:09)
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Start03.09 Video Scripts (8:49)
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Start03.10 Generate Text In Your Writing Style (3:25)
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Start04 01 Project Preview (1:51)
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Start04.02 Research-Chatgpt Usecase And Benefits (7:05)
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Start04.02 Research-More Examples And Explanation (7:49)
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Start04.03 Write An Article-Add Role To Chatgpt (7:17)
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Start04.03 Write An Article-Generate High Quality Content (8:02)
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Start04.04 Check Plagiarism (10:56)
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Start04.05 Prepare For Job Opportunities-Cv And Cover Letter (8:28)
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Start04.05 Prepare For Job Opportunities-Interview Questions, Connection And Task Generator (8:36)
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Start05 01 Project Preview (2:33)
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Start05.02 Generate Code-Javascript And Python Code Snippets (9:26)
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Start05.02 Generate Code-Stylesheet, Html, C++ And Conversion (9:20)
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Start05.03 Build Algorithms-Algorithm To Pseudocode (4:03)
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Start05.03 Build Algorithms-Realworld Use Cases (8:11)
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Start05.04 Debug-Python Use Case (6:51)
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Start05.04 Debug-React, Api, Javascript, Html And Css (6:56)
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Start05.05 Write Code Documentation (9:51)
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Start05.06 Use Chatgpt As A Linux Terminal (8:32)
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Start05.07 Use Chatgpt As A Unix Terminal (9:08)
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Start05.08 Use Chatgpt As A Microsoft Dos Terminal (5:28)
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Start05.09 Use Chatgpt To Suggest Uxui Designs (8:10)
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Start05.10 Use Chatgpt To Suggest Cybersecurity Solutions (10:05)
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StartSource Files
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Start01 Why All Developers Need To Know The Command Line (8:50)
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Start03 What Are Linux And Unix Terminals (8:04)
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Start01 What You-ll Need (1:20)
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Start02 Install Linux Command Line On Windows (3:18)
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Start01 Build Your First Command In The Command Line (3:48)
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Start02 Navigate Directories In The Command Line (6:33)
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Start03 Build And Edit A New File In The Command Line (7:27)
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Start04 Move Files In The Command Line (9:00)
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Start00. Introduction (4:42)
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Start02. Variables (19:17)
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Start03. Type Conversion Examples (10:04)
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Start04. Operators (7:04)
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Start05. Operators Examples (21:52)
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Start06. Collections (8:23)
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Start07. Lists (11:38)
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Start08. Multidimensional List Examples (8:05)
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Start09. Tuples Examples (8:34)
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Start10. Dictionaries Examples (14:24)
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Start11. Ranges Examples (8:30)
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Start12. Conditionals (6:41)
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Start13. If Statement Examples (10:16)
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Start14. If Statement Variants Examples (11:18)
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Start15. Loops (7:00)
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Start16. While Loops Examples (11:30)
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Start17. For Loops Examples (11:18)
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Start18. Functions (7:47)
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Start19. Functions Examples (9:16)
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Start20. Parameters And Return Values Examples (13:46)
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Start21. Classes And Objects (11:13)
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Start22. Classes Example (13:11)
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Start23. Objects Examples (9:54)
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Start24. Inheritance Examples (17:26)
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Start25. Static Members Example (11:03)
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Start26. Summary And Outro (4:06)
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Start01 Generate spreadsheet data with Auto-GPT (6:52)
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Start02 Format Excel spreadsheet with Auto-GPT (21:44)
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Start03 Manipulate data in Excel sheets with Auto-GPT (8:23)
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Start04 Replace data in Excel spreadsheet with Auto-GPT (9:23)
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Start05 Prevent data repetition in Excel with Auto-GPT (15:29)
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StartSource
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Start01 Generate Python Flask web app with Auto-GPT (7:32)
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Start02 Run Python web app with Flask (5:35)
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Start03 Send prompt from Python web app to ChatGPT (7:02)
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Start04 Test POST request from Python web app to ChatGPT (7:46)
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Start05 Show ChatGPT responses on Python Flask web app (6:20)
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Start06 Test sending ChatGPT response to custom web app (6:47)
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Start07 Show all ChatGPT messages in Flask (5:01)
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Start08 Test Auto-GPT code with virtual environment (4:53)
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StartSource
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Start01 Send POST requests to Flask app with Python (8:03)
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Start02 Handle JSON POST request data in Flask (10:21)
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Start03 Auto generate prompts with ChatGPT and Python (14:02)
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Start04 Auto refresh Flask app with HTML (4:31)
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Start05 Add personality and character to ChatGPT bots (8:23)
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StartSource
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Start00b-01 Openai Api Models To Work With (2:53)
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Start00b-02 How Openai Api Works (2:09)
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Start00b-03 Adjust Openai Api Model Parameters (7:58)
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Start01-01 Use Openai Api To Answer Questions Like Chatgtp (10:19)
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Start01-02 Correct Grammar With Openai Api (3:30)
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Start01-03 Summarize And Simplify Text With Openai Api (4:03)
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Start01-04 Translate Text With Openai Api (3:04)
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Start02-01 Generate Code With Openai Api (7:11)
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Start02-02 Explain Code With Openai Api (5:24)
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Start02-03 Calculate Time Complexity With Openai Api (3:40)
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Start02-04 Translate Programming Languages With OpenAI API (4:24)
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Start02-05 Fix Bugs In Code With Openai Api (3:19)
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Start03-01 Generate Sql Queries With Openai Py (5:15)
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Start03-02 Build Structured Table Data From Long Form Text (4:29)
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Start03-03 Classify Items Into Categories With Openai Api (4:50)
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Start03-04 Generate Spreadsheets And Lists With Chatgpt Openai Api (5:46)
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Start04-01 Convert Notes To Summary With Openai Api (5:40)
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Start04-02 Add Emotional Sentiment To Text With Openai Models (9:40)
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Start04-03 Generate Questions On A Topic With Gpt Turbo (9:26)
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Start04-04 Generate Text Conversation With Chatgpt Api (5:19)
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Start05-01 Classify Text Emotion Sentiment With Chatgpt Models (5:09)
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Start05-02 Extract Keywords From Text With Chatgpt Api (4:31)
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Start05-03 Convert Product Description To Ad With Chatgpt Python (3:57)
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Start05-04 Generate Product Names With Chatgpt In Python (4:04)
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Start05-05 Extract Information From Text With Chatgpt Api (2:57)
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Start06-01 Build Html Parser With Python (4:31)
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Start06-02 Scrape Hyperlinks From Url Webpage With Python (4:09)
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Start06-03 Filter Out Urls Not Part Of Domain (7:03)
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Start06-04 Save Web Content To Files With Python (10:07)
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Start07-01 Convert Text To Csv With Python (6:36)
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Start07-02 Remove Whitespace And Lines From Text With Python (4:58)
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Start07-03 Tokenize Text With Python For Machine Learning Models (2:50)
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Start07-04 Split Long Lines With Python (4:11)
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Start07-05 Split Pandas Dataframe Into Sections With Python (7:19)
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Start07-06 Embed Text For Machine Learning With Openai Api (8:05)
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Start08-01 Embed Question With Python (5:48)
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Start08-02 Answer Questions About Your Data With Customized Openai Model (10:36)
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Start09-01 Load And Read Pdf In Python (3:40)
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Start09-02 Build Vector Index From Pdf Text In Python (4:32)
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Start09-03 Answer Questions About Pdf With Chatgpt Model In Python (5:10)
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Start10-01 Generate Review Data With Chatgpt Api (8:14)
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Start10-02 Format Python Text To Multidimensional Pandas Dataframe (11:50)
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Start10-03 Change Column Data Type In Pandas Dataframe (2:40)
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Start10-04 Embed Text Data With Openai Api (6:25)
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StartSource files
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Start01-01 Why All Developers Need To Know The Command Line (8:50)
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Start01-02 What Are Linux And Unix Terminals (8:04)
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Start02-01 What You-ll Need (1:20)
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Start02-02 Install Linux Command Line On Windows (3:18)
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Start03-01 Build Your First Command In The Command Line (3:48)
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Start03-02 Navigate Directories In The Command Line (6:33)
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Start03-03 Build And Edit A New File In The Command Line (7:27)
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Start03-04 Move Files In The Command Line (9:00)
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StartSource Files
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Start00b-01 What Is Auto-GPT (2:53)
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Start00b-02 What You Need To Run Auto-Gpt (4:07)
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Start03-01 Install Auto-GPT_1 (5:50)
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Start03-02 Configure Auto-Gpt With Openai Api Key (5:07)
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Start04-01 Run Auto-Gpt To Automate Your First Task (13:05)
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Start04-02 Auto Build And Write Document With Auto-Gpt (13:26)
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Start04-03 Clean Text File With Auto-Gpt (6:42)
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Start05-01 Search The Web With Auto-Gpt (5:23)
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Start05-02 Research, Summarize And Save With Auto-Gpt (10:08)
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Start06B-01 Build A Website With Auto-Gpt (9:53)
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Start06B-02 Build A React Project With Auto-GPT (6:26)
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Start07-01 Scrape Site And Improve Product Description With Chat-GPT (16:34)
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StartSource Files
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Start08-01 Enable Plugins In Auto-GPT (9:35)
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Start08-02 How Auto-Gpt Plugins Work (6:01)
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Start09-01 Inject Os System Into Auto-GPT With System Info Plugin (3:55)
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Start09-02 Use System Info Plugin In Auto-GPT (2:38)
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Start10-01 Generate Twitter Consumer Key, Access Token And Client ID (3:55)
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Start10-02 Auto Post To Twitter With Auto-Gpt (4:21)
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Start10-03 Automate Replying To Tweets With Auto-GPT (2:17)
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Start10-04 Auto Read Tweets With Auto-Gpt (3:33)
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Start11-00 What Is Scenex Auto-GPT Plugin (3:56)
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Start11-01 Write Detailed Image Descriptions With Auto-Gpt And Scenex (5:55)
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Start12-01 Make App Password For Gmail Automation (1:31)
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Start12-02 Configure Auto-Gpt For Email Automation (4:13)
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Start12-03 Send Email With Auto-Gpt (10:13)
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Start12-04 Read And Respond To Emails With Auto-GPT (6:45)
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StartSource Files
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Start00 How To Become A Web Developer (7:40)
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Start01 HTML Basics (7:26)
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Start02 CSS Basics (5:50)
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Start03 Add Images To Website With HTML (9:13)
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Start04 Link To Pages With HTML Hyperlinks (5:30)
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Start05 Positioning Items On A Webpage With CSS Flexbox (11:32)
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Start06 Spacing Out Items With Flexbox (9:31)
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Start02.01 What is Google Colab (4:24)
-
Start00. Introduction (4:42)
-
Start02.02 What If I Get Errors (2:40)
-
Start02.03 How Do I Terminate a Session (2:40)
-
Start02. Variables (19:17)
-
Start03. Type Conversion Examples (10:04)
-
Start04. Operators (7:04)
-
Start05. Operators Examples (21:52)
-
Start06. Collections (8:23)
-
Start07. Lists (11:38)
-
Start08. Multidimensional List Examples (8:05)
-
Start09. Tuples Examples (8:34)
-
Start10. Dictionaries Examples (14:24)
-
Start11. Ranges Examples (8:30)
-
Start12. Conditionals (6:41)
-
Start13. If Statement Examples (10:16)
-
Start14. If Statement Variants Examples (11:18)
-
Start15. Loops (7:00)
-
Start16. While Loops Examples (11:30)
-
Start17. For Loops Examples (11:18)
-
Start18. Functions (7:47)
-
Start19. Functions Examples (9:16)
-
Start20. Parameters And Return Values Examples (13:46)
-
Start21. Classes And Objects (11:13)
-
Start22. Classes Example (13:11)
-
Start23. Objects Examples (9:54)
-
Start24. Inheritance Examples (17:26)
-
Start25. Static Members Example (11:03)
-
Start26. Summary And Outro (4:06)
-
StartSource code
-
Start01 Build Your First Flask App (13:26)
-
Start02 Render HTML On Multiple Pages (10:53)
-
Start03 Build Page Templates With HTML (9:31)
-
Start04 Build Dynamic Page Templates (5:36)
-
Start05 Display JSON Data (5:21)
-
Start06 Build A Template To Show All Data (9:16)
-
StartSource Files
-
Start01 What Is Http (5:35)
-
Start02 Http Request Types (5:55)
-
Start03 Elements Of Http Requests And Responses (4:19)
-
StartSource Code
-
Start16-01 Generate Python Flask Web App With Auto-GPT (7:38)
-
Start16-02 Run Python Web App With Flask (5:41)
-
Start16-03 Send Prompt From Python Web App To Chatgpt (7:07)
-
Start16-04 Test Post Request From Python Web App To Chatgpt (7:51)
-
Start16-05 Show Chatgpt Responses On Python Flask Web App (6:26)
-
Start16-06 Test Sending Chatgpt Response To Custom Web App (6:52)
-
Start16-07 Show All Chatgpt Messages In Flask (5:07)
-
Start16-08 Test Auto-Gpt Code With Virtual Environment (4:58)
-
Start17-01 Style Webpage With Auto-GPT And Bootstrap (8:13)
-
Start17-02 Test Web Style Built With Auto-GPT (7:22)
-
Start18-01 Send Post Requests To Flask App With Python (8:09)
-
Start18-02 Handle Json Post Request Data In Flask (10:27)
-
Start18-03 Auto Generate Prompts With Chatgpt And Python (14:07)
-
Start18-04 Auto Refresh Flask App With Html (4:36)
-
Start18-05 Add Personality And Character To Chatgpt Bots (8:28)
-
StartSource Files
-
Start01 Generate Web App With Form In Auto-GPT (6:23)
-
Start02 Configure Web App For Calendar (8:59)
-
Start19-00 Set Up Google Cloud Project (2:19)
-
Start19-01 Install Libraries With Pip (1:36)
-
Start19-02 Connect To Google Calendar Api With Auto-Gpt And Python (8:44)
-
Start19-03 Configure Redirect Url And Test Users In Google Cloud (5:06)
-
Start19-04 Fetch Google Calendar Events And Python (7:51)
-
Start21-01 Extract Datetime From Chat Message With ChatGPT (10:18)
-
Start21-02 Create Custom Google Calendar Event With Python (7:13)
-
Start21-03 Add Bootstrap Style And Calendar Embed (7:39)
-
StartSource Files
-
Start22-01 Download Auto-Gpt Plugins (4:25)
-
Start22-02 Build A Hello World Auto-Gpt Plugin (11:49)
-
Start22-03 Use Custom Plugin With Auto-Gpt (2:12)
-
Start22-04 Build Unit Tests For Auto-Gpt Plugin (5:51)
-
Start23-01 Build First Party Plugin Template In Auto-GPT (4:31)
-
Start23-03 Connect To Google Calendar Api In Auto-Gpt Plugin (5:46)
-
Start23-04 Hide Private Data With Environment Variables (9:01)
-
Start24-01 Get Upcoming Events With Google Calendar API (7:30)
-
Start24-02 Test Get Upcoming Events In Auto-Gpt (8:18)
-
Start25-01 Create Google Calendar Event In Custom Auto-GPT Plugin (4:51)
-
Start25-02 Create Calendar Event With Auto-Gpt (10:54)
-
StartSource Files
-
Start01.01 Course Requirement_1 (3:20)
-
Start02 01 Project Preview_1 (2:03)
-
Start02 02A Analyze Financial Statements Of Stock (9:00)
-
Start02 02B Financial Ratio And Trend Analysis (4:25)
-
Start02 03 Balance Sheet, Income Statement And Cash Flow Statement (9:00)
-
Start02 04 Loopholes And Weaknesses In Stock Financials (8:39)
-
Start02 05 Analyze Historical Stock Performance (11:16)
-
Start02 06 Predict Stock Performance (5:08)
-
Start02 07 Market Share_1 (5:31)
-
Start02 08 Industry Analysis (7:48)
-
Start02 09 Management Team Analysis (8:25)
-
Start02 10 Analyze Stock Risks (6:56)
-
Start02 11 Valuation (8:11)
-
Start02 12 Explain Business Model Of A Company (6:24)
-
Start02 13 Perform A Swot Analysis (8:16)
-
Start02 14 Summarize A Company’S Earnings Report Calls (6:55)
-
Start02 15 Evaluate A Company’S Esg Credentials (4:39)
-
Start03 01 Project Preview_1 (0:48)
-
Start03 02A Invest Short Term (6:22)
-
Start03 02B Implementing Your Short-Term Investment Strategy (8:06)
-
Start03 03A Invest Long Term (5:58)
-
Start03 03B Analyzing The Results (7:27)
-
Start03 04A Using Chatgpt To Assess Your Risk Tolerance (7:32)
-
Start03 04B Customized Investment Recommendations Based On Individual Financial Goals And Risk Tolerance (5:26)
-
Start03 04C Implementing Your Customized Investment Plan (8:47)
-
Start04 01 Project Preview_1 (1:25)
-
Start04.02A Recent Past Stock Market State (7:44)
-
Start04.02B Analyzing Past Trends And Economic Events (9:24)
-
Start04.03A Present Stock Market State (6:29)
-
Start04.04A Future Stock Market State (8:12)
-
Start04.04B Insights On Macroeconomic Factors (7:09)
-
Start05 01 Project Preview_1 (2:22)
-
Start05.02 Analyze Credit Scores (7:56)
-
Start05.03 Assess Loan Applicant Risk (7:35)
-
Start06 01 Project Preview_1 (1:12)
-
Start06.02A Pick Stocks With Company Evaluation (6:00)
-
Start06.03A Build A Trading Strategy (8:54)
-
Start06.03B Test Trading Hypthothesis (8:29)
-
Start07 01 Project Preview_1 (1:03)
-
Start07.02 Chatgpt And Sentiment Analysis (8:52)
-
Start07.03 Analyzing Sentiments On Social Media Posts- (8:45)
-
Start08 01 Project Preview_1 (1:03)
-
Start08.02A Fraud Detection With Chatgpt (7:37)
-
Start08.02B Detecting Exploitation Prone Weaknesses (8:01)
-
Start08.03A Red Flags And Anomaly Detection (6:07)
-
Start08.03B Anomaly Detection Techniques (8:01)
-
StartConclusion (2:20)
-
StartSource Files
-
Start00. Course Intro (6:10)
-
Start01. Intro To Tensorflow (5:33)
-
Start02. Installing Tensorflow (3:52)
-
Start03. Intro To Linear Regression (9:26)
-
Start04. Linear Regression Model - Creating Dataset (5:49)
-
Start05. Linear Regression Model - Building The Model (7:22)
-
Start06. Linear Regression Model - Creating A Loss Function (5:57)
-
Start07. Linear Regression Model - Training The Model (12:43)
-
Start08. Linear Regression Model - Testing The Model (5:22)
-
Start09. Summary And Outro (2:55)
-
StartIntro to Tensorflow - Source Files
-
Start00. Course Intro (6:05)
-
Start01. Quick Intro To Machine Learning (9:01)
-
Start02. Deep Dive Into Machine Learning (6:01)
-
Start03. Problems Solved With Machine Learning Part 1 (13:26)
-
Start04. Problems Solved With Machine Learning Part 2 (16:25)
-
Start05. Types Of Machine Learning (10:15)
-
Start06. How Machine Learning Works (11:40)
-
Start07. Common Machine Learning Structures (13:51)
-
Start08. Steps To Build A Machine Learning Program (16:34)
-
Start09. Summary And Outro (2:49)
-
StartIntro to Machine Learning Slides
-
Start00. Course Intro (5:11)
-
Start01. Intro To Numpy (6:21)
-
Start02. Installing Numpy (3:59)
-
Start03. Creating Numpy Arrays (16:55)
-
Start04. Creating Numpy Matrices (11:57)
-
Start05. Getting And Setting Numpy Elements (16:59)
-
Start06. Arithmetic Operations On Numpy Arrays (11:56)
-
Start07. Numpy Functions Part 1 (19:13)
-
Start08. Numpy Functions Part 2 (12:36)
-
Start09. Summary And Outro (3:01)
-
StartSource Files
-
Start00. Course Intro (6:19)
-
Start01. How Machines Interpret Text (15:23)
-
Start02. Building the Model Part 1 - Examining Dataset (12:27)
-
Start03. Building the Model Part 2 - Formatting Dataset (15:14)
-
Start04. Building the Model Part 3 - Building the Model (10:30)
-
Start05. Building the Model Part 4 - Training the Model (5:42)
-
Start06. Building the Model Part 5 - Testing the Model.mp4 (9:26)
-
Start07. Course Summary and Outro (3:29)
-
StartSource Files
-
Start00. Course Intro (5:30)
-
Start01. Intro to Pyplot (5:11)
-
Start02. Installing Matplotlib (5:51)
-
Start03. Basic Line Plot (7:53)
-
Start04. Customizing Graphs (10:47)
-
Start05. Plotting Multiple Datasets (8:10)
-
Start06. Bar Chart (6:26)
-
Start07. Pie Chart (9:13)
-
Start08. Histogram (10:14)
-
Start09. 3D Plotting (6:28)
-
Start10. Course Outro (4:09)
-
StartPyplot Code
-
Start00. Panda Course Introduction (5:43)
-
Start01. Intro To Pandas (7:55)
-
Start02. Installing Pandas (5:28)
-
Start03. Creating Pandas Series (20:34)
-
Start04. Date Ranges (11:29)
-
Start05. Getting Elements From Series (19:21)
-
Start06. Getting Properties Of Series (13:04)
-
Start07. Modifying Series (19:02)
-
Start08. Operations On Series (11:48)
-
Start09. Creating Pandas Dataframes (22:57)
-
Start10. Getting Elements From Dataframes (25:12)
-
Start11. Getting Properties From Dataframes (17:44)
-
Start12. Dataframe Modification (36:24)
-
Start13. Dataframe Operations (20:09)
-
Start14 Dataframe Comparisons And Iteration (15:35)
-
Start15. Reading Csvs (12:00)
-
Start16. Summary And Outro (4:14)
-
StartSource Files
-
Start00A What Is Machine Learning (5:26)
-
Start00B Types Of Machine Learning Models (12:17)
-
Start00C What Is Supervised Learning (11:04)
-
Start00D What Is Unsupervised Learning (8:17)
-
Start01 How Does A Machine Learning Agent Learn (7:38)
-
Start02 What Is Inductive Learning (4:11)
-
Start03 Performance Of A Machine Learning Algorithm (4:14)
-
Start04 Handle Noise In Data (5:22)
-
Start05 Powerful Tools With Machine Learning Libraries- (12:11)
-
Start01 Project Preview (3:29)
-
Start04-01 Create A Dataset (5:17)
-
Start04-02 Vectorize Text (16:27)
-
Start04-03 Build A Word Cloud (7:08)
-
Start04-04 Reduce Data Dimensionality With Principal Component Analysis (6:08)
-
Start04-05 Perform Unsupervised Classification With K-Means Clusters (17:33)
-
StartSource Files
-
Start01-01 Hash Table Or Dictionary Visualized With Time And Space Complexity (4:19)
-
Start01-02 Types Of Machine Learning (12:09)
-
Start01-03 What Is Supervised Learning (9:59)
-
Start01-04 What Is Unsupervised Learning (7:43)
-
Start02 What Machine Learning Can And Cannot Do (11:27)
-
Start03a-01 What Is Linear Regression (4:37)
-
Start03a-02 What Is Logistic Regression (3:54)
-
Start03a-03 Make Decisions With Decision Trees (10:31)
-
Start03b-01 What Is Deep Learning (5:44)
-
Start03b-02 What Is A Neural Network (7:07)
-
Start04 What Are Machine Learning Libraries (11:59)
-
Start00 Course Overview (13:46)
-
Start03-01 Probability And Information Theory Overview (5:15)
-
Start03-02 Combinatorics For Probability (8:44)
-
Start03-03 Law Of Large Numbers (10:38)
-
Start03-04 Calculate Center Of Distribution (7:40)
-
Start04-01 Uniform Distribution (5:25)
-
Start04-02 Gaussian Distribution (3:45)
-
Start04-03 Log-Normal Distribution (3:28)
-
Start04-04 Exponential Distribution (3:04)
-
Start04-05 Laplace Distribution (1:54)
-
Start04-06 Binomial Distribution (9:05)
-
Start04-07 Multinomial Distribution (3:59)
-
Start04-08 Poisson Distribution (4:21)
-
Start05 Calculate Error Of Machine Learning Model (8:44)
-
StartSource Files
-
Start00-00 What Is Python (4:48)
-
Start00-01. Intro To Python (4:37)
-
Start00b-00 Course Overview (3:26)
-
Start03-01 Load And Clean A Public Dataset (8:55)
-
Start03-01B What Is One-Hot Encoding (10:02)
-
Start03-02 Build X And Y Data With One Hot Encoding (4:57)
-
Start03-03 Logistic Regression With One Hot Encoding (2:20)
-
Start04-04 Scale And Encode Data With Scikit-Learn (3:47)
-
Start04-04 What Is Scaling Data (6:36)
-
Start04-05 Build, Train And Test A Machine Learning Model (4:37)
-
Start05-01 Compare Decision Tree And Linear Regression Models (6:26)
-
Start05-01C What Is The Kbins Discretizer (4:54)
-
Start05-02 Bin Data With Kbins Discretizer (3:42)
-
Start05-03 Compare Binned Regression Models (3:39)
-
Start05-04 Build A Linear Regression Model On Stacked Data (3:20)
-
Start05-05A What Is K Means Clustering (11:58)
-
Start06-01 Build Univariate Nonlinear Transformatio (1:55)
-
Start06-01 What Is Gaussian Probability Distribution- (2:31)
-
Start06-01B What Is Poisson Distribution (1:08)
-
Start06-02 Build X Y Data With Poisson Distribution In Numpy (3:34)
-
Start06-02C What Is Logarithmic Data Transformation (2:34)
-
Start06-03 Build A Ridge Regression Model (3:41)
-
StartSource Files - Course Overview
-
Start00. Course Intro (6:57)
-
Start01. Intro to Image Recognition (6:40)
-
Start02. Intro to MNIST (4:42)
-
Start03. Building a CNN Part 1 - Obtaining Data (15:40)
-
Start04. Building a CNN Part 2 - Building the Model (10:14)
-
Start05. Building a CNN Part 3 - Adding Loss and Optimizer Functions (4:57)
-
Start06. Building a CNN Part 4 - Train and Test Functions (10:58)
-
Start07. Building a CNN Part 5 - Train and Test the Model (9:17)
-
Start08. MNIST Image Recognition with Keras Sequential Model (13:24)
-
Start09. Summary and Outro (2:55)
-
StartSource Files
-
Start01 What You-ll Learn-1 (8:47)
-
Start01-01 Course Overview (3:30)
-
Start01-02 Build Models On The Web (5:06)
-
Start02 What Is Supervised Learning-2 (14:41)
-
Start02-01 What Are Search Algorithms (7:21)
-
Start02-02 Depth First Search (9:00)
-
Start02-02b Build A Depth First Search Algorithm (8:26)
-
Start02-03 What Is Breadth First Search (bfs) (5:08)
-
Start02-03b Build A Breadth First Search Algorithm (6:56)
-
Start02-04 Depth Limited Search (3:58)
-
Start02-05 Iterative Deepening Depth First Search (5:32)
-
Start02-06 What Is Uniform Cost Search (6:04)
-
Start02-06b Build A Uniform Cost Search Algorithm (8:07)
-
Start02-07 Bidirectional Search (4:44)
-
Start03 Build Models On The Web-3 (5:06)
-
Start03-01 What Are Informed Search Algorithms (4:07)
-
Start03-02 What Is Greedy Best-first Search (8:16)
-
Start03-02b Build A Greedy Best First Search Algorithm (10:43)
-
Start03-03 What Is A Search (5:10)
-
Start04-01 How Does A Machine Learning Agent Learn (7:37)
-
Start04-02 What Is Inductive Learning (4:10)
-
Start04-03 Make Decisions With Decision Trees (10:50)
-
Start04-04 Performance Of A Machine Learning Algorithm (4:13)
-
Start04-05 Handle Noise In Data (5:20)
-
Start04-06 Statistical Learning (3:56)
-
Start05-01 What Is Logistic Regression (4:26)
-
Start05-03 Prepare Data For Logistic Regression (12:19)
-
Start05-03a How To Prepare Data (8:52)
-
Start05-04 Build A Logistic Regression Model (5:29)
-
Start05-04a How To Build A Logistic Regression Model (3:28)
-
Start05-04b What Is Optimization (12:10)
-
Start05-05 Optimize The Logistic Regression Model (12:44)
-
Start05-05a How To Optimize A Logistic Regression Model (12:45)
-
Start05-06 Train The Model (10:09)
-
Start05-07 Test The Model (2:33)
-
Start05-08 Visualize Results (5:38)
-
Start06.01 What Is Gradient Boosting-1 (1:54)
-
Start06.02 Prepare Data For Gradient Boosted Classification-2 (7:19)
-
Start06.03 Build Binary Classes-3 (6:12)
-
Start06.04a How To Shape Data For Classification-4 (2:58)
-
Start06.04b Shape Data For Classification-5 (7:06)
-
Start06.05a How To Build A Boosted Trees Classifier-6 (4:03)
-
Start06.05b Build A Boosted Trees Classifier-7 (4:37)
-
Start07.01 Build Input Functions-1 (3:55)
-
Start07.02 Build A Boosted Trees Regressor-2 (3:02)
-
Start07.03 Train And Evaluate The Model-3 (4:07)
-
StartSource Files
-
Start01-01 Build Patterns And Responses Training Data (6:34)
-
Start01-02 Tokenize Chat Data For Training (4:30)
-
Start02-01 Clean Chat Data For Machine Learning (3:04)
-
Start02-02 Build Bag Of Words For Ml Model (4:24)
-
Start02-03 Split Data For Machine Learning (3:34)
-
Start03-01 Build A Tensorflow Machine Learning Model For Chat (4:54)
-
Start03-02 Test Chatbot Machine Learning Model (9:09)
-
Start03-03 Categorize Chat Question With Ml (7:25)
-
Start03-04 Pick A Chatbot Response In Top Category (8:18)
-
StartSource Files
-
Start00-01 Introduction to Transformer Neural Networks (4:31)
-
Start00-02 Transformer Project Overview (7:59)
-
Start01-01 Connect To Google Drive Dataset In Colab (3:48)
-
Start01-02 Read Text Files In Python (9:17)
-
Start01-03 Read Movie Conversation Text File In Python (10:58)
-
Start01-04 Clean Text Data For NLP (6:09)
-
Start01-05 Remove Contractions From Text Data With Python (9:35)
-
Start01-06 Preprocess Text Data For Transformer Chatbot Ml (6:16)
-
Start02-01 Build Tokenizer With Tfds (7:31)
-
Start02-02 Add Padding To Tokenized Sentences With Python (3:06)
-
Start02-03 Build Tensorflow Dataset For ML (3:13)
-
Start03-01 Calculate Scaled Dot Product Attention (4:56)
-
Start03-02 Set Up Multi Head Attention Layer In Python Nn (5:22)
-
Start03-03 Split Attention Layer Into Multiple Heads (4:08)
-
Start03-04 Add Scaled Dot Product Attention And Final Layer (5:22)
-
Start04-01 Mask Padding Tokens With Python (4:38)
-
Start04-02 Build Lookahead Mask For Future Tokens (3:53)
-
Start05-01 Set Up Positional Encoding Layer In Neural Network (3:03)
-
Start05-02 Build Positional Encoding Layer With Tensorflow Keras (5:31)
-
Start06-01 Build Input Encoder For Neural Network (5:28)
-
Start06-02 Combine Input And Positional Encoding (5:36)
-
Start07-01 Set Up Decoder Layer With Python (6:31)
-
Start07-02 Combine Output And Positional Encoding For Decoder (5:28)
-
Start08-01 Combine encoding and decoding in NN (7:08)
-
Start08-02 Build custom ML model learning rate (3:37)
-
Start08-03 Build custom model loss function (3:17)
-
Start08-04 Compile neural network with Python (4:30)
-
Start08-04b Zero out padding tokens in attention (1:44)
-
Start08-05 Limit and pad tokenized sentences (5:30)
-
Start09-01 Handle new chatbot question input (5:13)
-
Start09-02 Decode tokens into words (2:30)
-
StartSource files
-
Start01-01 Projects Preview (4:49)
-
Start01-01 What Is Natural Language Processing (5:39)
-
Start01-02 What Is Text Vectorization (7:34)
-
Start03-01 Train A Vectorizer (8:50)
-
Start03-02 Chat With The User (11:04)
-
Start04-01 Define A Basic Intent Classifier (7:42)
-
Start04-02 Define A Basic Generative Model (4:05)
-
Start04-03 Test The Chatbot (9:33)
-
StartSource Files
-
Start01-00 Course Overview - Text To Speech (1:13)
-
Start01-01 How Text To Speech Works (5:43)
-
Start01-02 What You-ll Need - Text To Speech (3:25)
-
Start03-01 Convert Text To Speech With Gtts (5:45)
-
Start04-00 What Are Pytorch, Tacotron 2 And Waveglow (4:29)
-
Start04-01 Load Models (3:50)
-
Start04-02 Convert Text To Speech With Pytorch (7:45)
-
Start05-00 What Is Pyttsx3 (1:20)
-
Start05-01 Load Available Voices (4:32)
-
Start05-02 Convert Text To Speech With Pyttsx3 (4:48)
-
StartSource Files
-
Start00 01 Introduction Of The Instructor (1:53)
-
Start01.01 Setting Up Your Chatgpt Account - A Step-By-Step Guide (6:04)
-
Start01.02 Tips For Getting The Best Responses From Chatgpt (9:55)
-
Start02 01 Building A Marketing Campaign Content Calendar With Chatgpt (10:34)
-
Start03 01 The Importance Of Identifying Your Target Audience_1 (3:08)
-
Start03.02 Using Chatgpt For Target Audience Research And Assessment (11:54)
-
Start01. Source Files
-
Start04 01 Project Preview (1:21)
-
Start04.02 Exploring Social Media Marketing And Automation (5:59)
-
Start04.03 Generating Social Media Posts (10:38)
-
Start04.04 Social Media Automation Tool - Socialbee - -Bonus- (6:40)
-
Start04.05 Automating Social Media Post Scheduling - -Bonus- (8:26)
-
Start04.06 Automating Social Media Reposting - -Bonus- (8:28)
-
Start04.07 Configuring Your Social Media Automation Timetable – -Bonus- (4:00)
-
Start05 01 Project Preview (1:11)
-
Start05.02 Generate Optimized Keywords And Blog Headlines (7:39)
-
Start05.03 Building An Seo-Enhanced Blog Post Quickly (10:07)
-
Start02. Source Files
-
Start06 01 Introduction To Email Marketing And Its Significance_1 (3:37)
-
Start06.02 Building Effective Email Sequences (7:27)
-
Start07 01 Crafting Sales Page Copy (8:05)
-
Start08 01 Project Preview (1:07)
-
Start08.02 Producing Facebook Ads (10:00)
-
Start08.03 Generating Google Ads (9:44)
-
Start08.04 Generate Ads For Instagram And Twitter (7:36)
-
Start09 01 Project Preview (1:09)
-
Start09.02 Generating Unlimited Video Concepts (10:33)
-
Start09.03 Crafting A Full Youtube Video Script (10:00)
-
Start09.04 Youtube Seo Strategies (8:54)
-
Start03 Source Files
-
Start10 01 Project Preview (1:26)
-
Start10.02 Guides To Building Effective Marketing Funnels (4:01)
-
Start10.03 Defining Your Buyer Persona (9:38)
-
Start10.04 Generating A Lead Magnet (8:57)
-
Start10.05 Building Landing Page And Social Media Copy (9:02)
-
Start10.06 Composing A Comprehensive Email Sequence For Your Funnel (4:49)
-
Start11 01 Review Analysis And Optimization Of Products And Services (7:24)
-
Start04. Source Files
-
Start12 01 Project Preview (1:57)
-
Start12.02 Homepage, About Us, And Contact Us Page Copy (10:14)
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Start12.03 Generate Meta Title And Descriptions (4:58)
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Start12.04 Website Development With Chatgpt Crash Course (25:32)
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Start13 01 Project Preview (1:10)
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Start13.02 Creating Product And Business Names (7:52)
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Start13.03 Developing Professional Taglines And Slogans For Your Brand (7:32)
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Start13.04 Writing Product Descriptions For Your Online Store (4:46)
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Start13.05 Building Faq’S For Services Or Products (4:54)
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Start14 01 Conclusion (2:08)
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StartBonus - Tips And Tricks (7:43)
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Start05. Source Files
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Start01 01 Course Requirement (2:31)
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Start02 01 Project Preview (1:36)
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Start02.02A Set Up Excel Spreadsheet With Gpt Add-In (8:37)
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Start02.02B Excel With Chatgpt (4:51)
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Start02.03 Write Excel Formulas With Chatgpt (9:39)
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Start02.04 Use Chatgpt Formulas In Excel (16:18)
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Start03 01 Project Preview (1:27)
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Start03.02A Set Up Dashboard (7:51)
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Start03.02B Set Up Data (7:11)
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Start03.03A Use Chatgpt And Excel To Build An Investment Dashboard (11:37)
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Start03.03B Generate More Formulas For Excel (11:34)
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Start03.03C Placing Data On Dashboard (10:30)
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Start04 01 Project Preview_1 (2:10)
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Start04.02A Project Setup - Product Worksheet (11:59)
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Start04.02B Setup Sales And Summary Sheet (9:22)
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Start04.03A Build Advanced Chatgpt Excel Project (13:00)
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Start04.03B Automating Product Name And Price Data (13:11)
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Start04.03C Completing Sales Sheet Automation With Chatgpt (9:32)
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Start04.03D Building Sales Overview Dashboard (8:37)
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Start04.03E Refining The Pos System (11:14)
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Start05 01 Project Preview_1 (2:18)
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Start05.02 Meeting Agendas And Minutes (10:25)
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Start05.03 Write A Business Proposal (11:18)
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Start05.04 Build A Business Report (11:12)
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Start05.05 Build A Business Plan (10:35)
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Start05.06 Build A Business Performance Appraisal (10:39)
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Start05.07 Build A Business Presentation (12:40)
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Start05.08 Summarize Business Documents (11:44)
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Start05.09 Write Job Descriptions (8:33)
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Start05.10 Build White Papers (9:38)
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Start05.11 Build Employee Handbooks (8:44)
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Start05.12 Build Business Manuals (9:24)
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Start06 01 Project Preview_1 (1:16)
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Start06.02 Set Up Project (8:06)
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Start06.03A Advanced Chatgpt 4 Business Project (10:10)
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Start06.03B Chatgpt And Social Bee Side By Side (10:16)
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Start06.03C Finishing Touches (12:26)
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StartSource Files
-
Start01. Course Requirements (2:56)
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Start02. What Is Jsbin (3:15)
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Start03. Setting Up The Html Document (2:41)
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Start04. Header Tags And Paragraphs Tags (4:06)
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Start05. Styles (3:32)
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Start06. Bold Underline And Italic Tags (3:10)
-
Start07. Adding In A Link (1:38)
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Start08. Adding In A Image (3:01)
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Start09. Adding A Link To An Image (1:55)
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Start10. Lists (4:03)
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Start11. Tables (3:29)
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Start12. Different Kinds Of Input (4:59)
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Start13. Adding In A Submit Button (3:01)
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Start14. Scripts And Style Tags (3:27)
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Start01. Course Requirements (3:41)
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Start02. Html Styles Crash Course (4:45)
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Start03. Adding Code To The CSS (4:46)
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Start04. Adding In IDs To The CSS (5:16)
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Start05. Classes In CSS (2:39)
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Start06. Font Families (5:04)
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Start07. Colors In CSS (5:44)
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Start08. Padding In CSS (3:06)
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Start09. Text Align And Transforms (3:14)
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Start10. Margins And Width (5:33)
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Start11. Changing The Body (4:11)
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Start12. Latin Text Generator (1:57)
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Start13. Adding In A Horizontal Menu With HTML And CSS (7:53)
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Start14. Adding A Background Image (4:04)
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Start15. Playing Around With Margins In CSS (2:20)
-
Start01. Variables (5:36)
-
Start02. Javascript (10:24)
-
Start03. Numbers (4:52)
-
Start04. Booleans (5:22)
-
Start05. If Statements (4:27)
-
Start06. Arrays (8:31)
-
Start07. For Loops (9:16)
-
Start08. While Loops (4:34)
-
Start09. Objects (8:02)
-
Start10. Functions (6:09)
-
Start11. Foreach (3:54)
-
Start12. Map Functions (5:22)
-
Start13. Using Objects As Dictionary (2:45)
-
Start14. Switch Statements (6:38)
-
Start15. Destructuring (5:30)
-
Start16. Spread Operator (6:56)
-
Start17. String Templates (6:37)
-
Start18. Error Handling (5:45)
-
Start19. Let And Const Keywords (3:39)
-
Start20. Do-While (1:45)
-
Start21. Sets (5:42)
-
Start22. Maps (4:39)
-
Start23. Stacks (6:06)
-
Start24. Queues (11:49)
-
Start25. For Loop (5:11)
-
Start26. Recursive Functions (7:13)
-
Start27. Loop Labeling (5:18)
-
Start28. 2D Arrays (21:59)
-
Start29. Settimeout (7:02)
-
Start30. Sentimental (11:21)
-
Start31. Functions With Optional Parameters (15:10)
-
Start32. Basic Regular Expression (5:53)
-
Start33. Handle Keypress Events (22:45)
-
Start34. Priority Queue (15:54)
-
Start35. Add-delete Object Property (2:45)
-
Start36. Example With Sets Part 1 (28:49)
-
Start36. Example With Sets Part 2 (43:20)
-
Start37. Concat (3:12)
-
Start38. Flat And Flatmap (2:06)
-
Start01-01 Why All Developers Need To Know The Command Line (8:50)
-
Start01-02 What Are Linux And Unix Terminals (8:04)
-
Start02-01 What You-ll Need (1:20)
-
Start02-02 Install Linux Command Line On Windows (3:18)
-
Start03-01 Build Your First Command In The Command Line (3:48)
-
Start03-02 Navigate Directories In The Command Line (6:33)
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Start03-03 Build And Edit A New File In The Command Line (7:27)
-
Start03-04 Move Files In The Command Line (9:00)
-
StartSource Files
-
Start00-Course Preview (4:02)
-
Start01 Why Use The Cloud For Machine Learning (2:38)
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Start02 Benefits Of Cloud Computing- (1:23)
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Start03 Public Vs Private Cloud Computing (3:18)
-
Start04 Managed Vs Unmanaged Cloud Computing (1:30)
-
Start05 Iaas Vs Paas Vs Saas In Cloud Computing (3:33)
-
Start06 Google Cloud Vs Aws Vs Azure For Machine Learning (3:32)
-
Start07 Build A Google Cloud Project For Machine Learning (6:45)
-
Start08 What Is A Service Account In Google Cloud Platform (1:59)
-
Start09 Build A Service Account And Key In Google Cloud (6:52)
-
Start10 Image Dataset For Machine Learning From Cloud Storage (2:12)
-
Start12 Build An Image Dataset For Classification From A Cloud Storage Bucket (5:36)
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Start13 Train An AutoML Image Classifier Machine Learning Model (6:27)
-
Start14 Deploy Machine Learning Model To Cloud Endpoint (3:38)
-
Start15 Make A Prediction With A Cloud Machine Learning Model (5:14)
-
Start16 Sign In To Google Cloud (2:46)
-
Start17 Build A Bigquery Dataset In Google Cloud Console (8:24)
-
Start18 Build A Cloud Storage Bucket In Google Cloud (8:15)
-
Start19 What Is Dataflow API In Google Cloud (2:44)
-
Start20 What Is Pubsub In Google Cloud (4:24)
-
Start21 Build Data Streaming Dataflow Pipeline With Google Cloud Api (9:39)
-
Start22 Analyze Streaming Data With Bigquery Google Standard Sql (6:39)
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Start23 Visualize Bigquery Cloud Data With Google Data Studio (3:54)
-
StartSource Files
-
Start00A Course Overview (3:09)
-
Start00A-01 What Is Microsoft Azure Machine Learning (3:24)
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Start00A-02 What Is Microsoft Certified Azure Data Scientist Associate (5:10)
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Start02-01 Why Use The Cloud For Machine Learning (2:38)
-
Start02-03 Public Vs Private Cloud Computing (3:18)
-
Start02-04 Managed Vs Unmanaged Cloud Computing (1:30)
-
Start02-05 Iaas Vs Paas Vs Saas In Cloud Computing (3:33)
-
Start02-06 Google Cloud Vs Aws Vs Azure For Machine Learning (3:32)
-
Start03 What Is Azure Machine Learning Studio (2:17)
-
Start04-01 Build An Azure Machine Learning Workspace (12:51)
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Start04-02 Build A New Compute Cluster In Microsoft Azure Ml (6:08)
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Start04-03 Build A Pipeline In Microsoft Azure Ml Designer (4:25)
-
Start04-03A What Is Azure Machine Learning Designer (3:16)
-
Start05-01 Build A Dataset In Microsoft Azure Ml Designer (3:48)
-
Start05-02 Clean Missing Data In Microsoft Azure Ml Designer (10:26)
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Start05-03 Normalize Data In Microsoft Azure Ml Studio (4:24)
-
Start05-04 Run A Data Transformation Pipeline In Microsoft Azure Ml Designer (2:09)
-
Start06-00 What Is Linear Regression (5:03)
-
Start06-01 Build A Model Training Pipeline In Microsoft Azure Ml Studio (5:03)
-
Start06-02 Evaluate A Machine Learning Model In Microsoft Azure Ml (7:08)
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StartSource Files
-
Start00-01b What You-ll Learn (7:12)
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Start00-02 What Is Tensorflow Js (4:28)
-
Start00-03 Load Tensorflow Object (4:28)
-
Start01 What Is Machine Learning (6:39)
-
Start01b-01 Build A Scatter Plot (8:41)
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Start01b-02 Build A Bar Chart (5:33)
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Start01b-03 Build A Histogram (6:39)
-
Start01c-01 Build Sample Data (5:16)
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Start01c-02 Build The Model (11:14)
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Start01c-03 Make A Prediction (7:47)
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Start01d-01 Generate Data (13:38)
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Start01d-02 Visualize Data (16:10)
-
Start02-00 What Is Linear Regression (7:52)
-
Start02-01 Prepare Training Data (7:10)
-
Start02-02 Build The Model (14:05)
-
Start02-03 Make A Prediction (3:53)
-
Start02b-01 Set Up The Canvas (3:48)
-
Start02b-02 Draw A Data Sample (6:20)
-
Start02b-03 Create Loss And Prediction Functions (6:00)
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Start02b-04 Collect User Input For Data (8:50)
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Start02b-05 Visualize Linear Regression With Dynamic Data (6:46)
-
Start03-01 Set Up The Canvas (11:00)
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Start03-02 Visualize Linear Regression With Dynamic Data (16:33)
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Start04-01 Generate Samples (6:21)
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Start04-02 Generate A Prediction Equation With Weights (6:54)
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Start04-03 Train The Model (5:26)
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Start04-04 Visualize Predictions (18:01)
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Start04-05 Visualize Prediction Error (10:00)
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Start05-01 Load Models Into Html (5:51)
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Start05-02 Train Model On Images (13:13)
-
Start05-03 Make A Prediction (6:58)
-
StartSource Files
-
Start00 What You-ll Learn (7:44)
-
Start04-00a What Is Deep Learning (6:08)
-
Start04-00b What Is A Neural Network (8:06)
-
Start04-01 Build A Perceptron (13:26)
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Start04-02 Build A Sigmoid Function (8:01)
-
Start04-03 Build A Sigmoid Perceptron (7:35)
-
Start04-04 Build A Relu Activation Function (7:12)
-
Start04-05 Build A Leaky Relu Activation Function (6:10)
-
Start05-01 Build Neural Network Layers (9:57)
-
Start05-02 Train And Test The Neural Network (11:24)
-
Start06-01 Build A Dataset-1 (8:26)
-
Start06-02 Build A Neural Network-2 (5:35)
-
Start06-03 Train The Neural Network-3 (10:05)
-
Start06-04 Make A Prediction With The Neural Network-4 (8:43)
-
Start07-00 What Is Cross Validation-1 (8:24)
-
Start07-01 Load A Model Into Html-2 (4:57)
-
Start07-02 Use A Neural Network In Your Website-3 (8:49)
-
Start07-03 Show Neural Network Results On Website-4 (5:34)
-
Start08-01 Build A Dataset For Xor (6:32)
-
Start08-02 Build A Neural Network For Xor (5:19)
-
Start08-03 Train And Test The Neural Network (11:06)
-
Start09-01 Load An Rnn Into Your Website (5:37)
-
Start09-02 Set Up The Canvas (7:06)
-
Start09-03 Draw With A Neural Network (8:50)
-
Start10-01 Load An Image For Object Detection (6:13)
-
Start10-02 Load A Neural Network For Object Detection (6:15)
-
Start10-03 Outline Objects In The Image (12:17)
-
Start11-01 Build A Deep Neural Network With Gradient Descent From Scratch-1 (9:21)
-
Start11-03 Build A Deep Neural Network With Gradient Descent With Tensorflow Js-2 (11:24)
-
Start11-04 Build A Deep Neural Network With Backpropagation-3 (7:03)
-
Start11-05 Build The Backpropagation-4 (16:56)
-
Start12-01 Reduce Neural Network Error-1 (17:12)
-
Start12-02 Build A Gradient Descent Algorithm-2 (8:48)
-
Start13 Train The Deep Neural Network With Gradient Descent (15:24)
-
StartTensorflow JS Source Files
-
Start02-01 Load The Model With Text (4:18)
-
Start02-02 View Model Results Of Text Toxicity (6:40)
-
Start02-03 Clean Up Prediction Results (6:18)
-
Start03-01 Set Up The Speed Recognition Model (6:00)
-
Start03-02 Set Up The Canvas (3:26)
-
Start03-03 Classify Words Through Microphone (6:55)
-
Start03-04 Draw From User Commands (7:35)
-
Start03-05 Optimize The Drawing (5:53)
-
Start04-01 Tidy Tensors (6:26)
-
Start04-02 Keep Tensors (3:10)
-
Start04-03 Dispose Tensors (2:41)
-
Start04-04 Build A Memory Leak Example (4:35)
-
Start05-01 Load Json Data (7:34)
-
Start05-02 Convert Json Data To Tensor (9:08)
-
Start05-03 Visualize Dataset With Tf-Vis (5:38)
-
Start05-04 Build And Train Model (10:22)
-
Start05-05 Visualize Model-s Training Epochs (9:12)
-
Start05-06 Make A Prediction (13:49)
-
Start05-07 Visualize Prediction (9:09)
-
Start06-01 Load Dataset From Json File (6:48)
-
Start06-02 Visualize Dataset-s Features (9:26)
-
Start06-03 Build A Multi Layer Model (7:43)
-
Start06-04 Extract Inputs And Outputs (7:10)
-
Start06-05 Normalize Data (4:47)
-
Start06-06 Train The Model (6:01)
-
Start06-07 Evaluate Model Performance (6:12)
-
Start07-00 What Is Logistic Regression (4:32)
-
Start07-00B Calculate Logistic Regression Accuracy (5:20)
-
Start07-01 Build A Logistic Regression Model (7:08)
-
Start07-02 Train The Logistic Regression Model (15:20)
-
Start07-03 Visualize Logistic Regression Results (12:52)
-
Start07-04 Visualize Original Data (12:13)
-
Start07-05 Visualize Model Error (7:37)
-
Start08-00 What Is Fast Fourier Transform (2:42)
-
Start08-01 Build And Visualize A Dataset (10:48)
-
Start08-02 Visualize Frequencies With Fast Fourier Transform (11:53)
-
Start08-03 Visualize Inverse Fast Fourier Transform (5:44)
-
Start09-00 What Is Principal Component Analysis (6:13)
-
Start09-01 Build Principal Component Analysis (6:24)
-
Start09-02 Calculate Variance Of Data And Principal Component Analysis (9:28)
-
Start09-03 Visualize Data Slices (12:01)
-
Start09-04 Visualize Principal Component Analysis Results (3:03)
-
StartSource Files
-
Start00B What Is A Neural Network (8:08)
-
Start00A What Is Deep Learning (6:10)
-
Start02-00 What Is One Hot Encoding (6:53)
-
Start02-01 Build Training Data (7:34)
-
Start02-02 Build The Neural Network (6:48)
-
Start02-03 Train The Neural Network (9:33)
-
Start02-04 Make A Prediction (10:11)
-
Start03-01 Build Training Data To Represent Images (12:15)
-
Start03-02 Build The Convolutional Neural Network (10:39)
-
Start03-03 Train The Convolutional Neural Network (9:06)
-
Start03-04 Make A Prediction Of Number Of Lines (15:05)
-
Start04-00 What Is A Recurrent Neural Network (6:38)
-
Start04-01 Generate Sequence And Label (6:25)
-
Start04-02 Generate Dataset (6:02)
-
Start04-03 Build The Lstm Model (4:55)
-
Start04-04 Train The Model (11:25)
-
Start06-01 Process Iris Data (7:37)
-
Start06-02 Convert Data To Tensors (8:45)
-
Start06-03 Separate Training And Testing Data (8:54)
-
Start06-04 Create Training And Testing Datasets (4:42)
-
Start06-05 Build The Model (9:29)
-
Start06-06 Train The Model (4:11)
-
Start06-07 Make A Prediction (8:45)
-
Start07-01 Load Model And Dataset (5:57)
-
Start07-02 Get User Input For Sentiment Analysis (10:59)
-
Start07-03 Make A Prediction (7:11)
-
Start08-00 What Is A Convolutional Neural Network (19:29)
-
Start08-01 Set Up Canvas To Load Image Data (10:36)
-
Start08-02 Load Mnist Dataset (6:47)
-
Start08-03 Separate Training And Testing Data (5:40)
-
Start08-04 Build The Model (6:48)
-
Start08-04A What Are The Network-s Layers (14:14)
-
Start08-05 Train The Model (11:27)
-
Start08-06 Create Training Batches (6:14)
-
Start08-07 Create Testing Batches (11:31)
-
Start08-08 Fit Neural Network Through Data (8:54)
-
StartSource Files
-
Start01. Downloading And Installing Android Studio (6:53)
-
Start00. Introduction (3:27)
-
Start02. Exploring Android Studio Interface (12:59)
-
Start03. Understanding File Hierarchy (12:19)
-
Start04. Exploring Activity-Layout Relationship (19:36)
-
Start05. Setting Up An Emulator (7:01)
-
Start06. Running App And Implementing User Interaction (6:45)
-
Start07. Debugging An App (6:11)
-
Start08. Summary And Outro (4:07)
-
StartSource Files
-
Start01. Introduction To Variables (7:04)
-
Start00. Introduction (6:12)
-
Start02. Basic Operations (9:18)
-
Start03. Nullable Variables (5:24)
-
Start04. Collections Intro (7:27)
-
Start05. Mutable Lists And Arrays (6:53)
-
Start06. If Statements And Expressions (8:11)
-
Start07. When Statements And Expressions (3:30)
-
Start08. While Loops (6:46)
-
Start09. For In Loops (4:55)
-
Start10. Introduction To Functions (7:55)
-
Start11. Functions With Parameters And Return Values (7:29)
-
Start12. Classes And Objects Introductions (16:37)
-
Start13. Subclassing And Superclassing (13:12)
-
Start14. Summary And Outro (4:41)
-
StartSource FIles
-
Start00-01 What You-ll Need (4:29)
-
Start00-00 Course Overview (3:12)
-
Start04b Project Preview (2:17)
-
Start05-01 Build A Linear Regression Model With Python (15:06)
-
Start05-02 Convert Python Model To Tensorflow Lite (5:38)
-
Start06-03 Build A New Android Studio App (7:39)
-
Start06-04 Build App Layout (10:18)
-
Start07-05 Load Machine Learning Model (4:53)
-
Start07-06 Use Machine Learning Model (5:18)
-
Start07-07 Connect App Layout To Model (6:08)
-
Start08-00 Project Preview (1:49)
-
Start08-00 What Is Logistic Regression (4:32)
-
Start09-01 Load And Process Data For Logistic Regression With Scikit Learn (9:14)
-
Start09-02 Build A Logistic Regression Model With Python (8:01)
-
Start09-03 Convert Logistic Regression Model To Tensorflow Lite (2:38)
-
Start10-04 Build A New Android Studio App With Tf Lite Model (5:48)
-
Start10-05 Build App Layout For Logistic Regression (9:26)
-
Start11-06 Load Logistic Regression Model In Android Studio (5:01)
-
Start11-07 Use Logistic Regression Model In Android (8:46)
-
Start11-08 Enable App User Interaction With Machine Learning Model (9:54)
-
StartSource files
-
Start00-01 What You-ll Need (5:56)
-
Start00-00 Course Overview (6:54)
-
Start00-02 What Is Coreml (6:43)
-
Start01-00A What Is Sentiment Analysis (4:39)
-
Start01-00B Natural Language Framework (4:32)
-
Start01-01 Build A New Swiftui App For Sentiment Analysis (8:59)
-
Start01-02 Perform Sentiment Analysis In SwiftUI (7:38)
-
Start01-03 Change Color Depending On Sentiment (4:56)
-
Start02-01 Train A Model With CreateML (12:13)
-
Start02-02 Test The Model With CoreML In An App (14:17)
-
Start02-03 Display Prediction Accuracy (6:41)
-
Start03-01 What Is Deep Learning (6:10)
-
Start03-02 What Is A Neural Network (8:08)
-
Start04-01 Load A CoreML Model Into A New Xcode Project (11:00)
-
Start04-02 Add Images For Classification (6:31)
-
Start04-03 Enable User To Loop Through Image (5:40)
-
Start04-04 Import CoreML Model Into The View (5:28)
-
Start04-05 Resize Image For Model (6:26)
-
Start04-05A Resizing Image Overview (7:44)
-
Start04-06 Convert Image To Buffer For Model (8:55)
-
Start04-06A Image To Buffer Overview (6:55)
-
Start04-07 Test The Model On Image Classification (14:31)
-
Start05-00 Tip - How To Unhide Library Folder (1:22)
-
Start05-01 Build A New Xcode Project To Compile Model (4:44)
-
Start05-02 Build A Playground With Object Detection Model (4:28)
-
Start05-03 Instantiate A Model 05-Object (6:12)
-
Start05-04 Build An Image Analysis Request (7:23)
-
Start05-05 Resize Image For Model (9:36)
-
Start05-06 Convert Image To Buffer For Model (9:47)
-
Start05-07 Test Object Detection On Image (4:53)
-
StartSource Files
-
Start2) 2nd Hour - Functions In R (54:57)
-
Start1) 1st Hour - Course Overview And Data Setup (57:35)
-
Start3) 3rd Hour - Regression Model (63:39)
-
Start4) 4th Hour - Regression Models Continued And Classification Models (57:04)
-
Start5) 5th Hour - Classification Models Continued, Rmark Down And Excel (78:31)
-
StartSource Files