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TensorFlow.js Neural Networks: Advanced Techniques and Applications
Mammoth Interactive Courses Introduction
Preface
01. About Mammoth Interactive (1:12)
02. How To Learn Online Effectively (13:46)
Source Files
(Prerequisite) Introduction to HTML
01. Course Requirements (2:55)
02. What Is JSbin (3:15)
03. Setting Up The HTML Document (2:41)
04. Header Tags And Paragraphs Tags (4:06)
05. Styles (3:32)
06. Bold Underline And Italic Tags (3:10)
07. Adding In A Link (1:38)
08. Adding In A Image (3:00)
09. Adding A Link To An Image (1:54)
10. Lists (4:03)
11. Tables (3:29)
12. Different Kinds Of Input (4:59)
13. Adding In A Submit Button (3:01)
14. Scripts And Style Tags (3:27)
(Prerequisite) Introduction to CSS
01. Course Requirements (3:41)
02. Html Styles Crash Course (4:45)
03. Adding Code To The CSS (4:46)
04. Adding In Ids To The CSS (5:16)
05. Classes In CSS (2:39)
06. Font Families (5:04)
07. Colors In CSS (5:44)
08. Padding In CSS (3:06)
09. Text Align And Transforms (3:14)
10. Margins And Width (5:33)
11. Changing The Body (4:11)
12. Latin Text Generator (1:57)
13. Adding In A Horizontal Menu With HTML And CSS (7:53)
14. Adding A Background Image (4:04)
15. Playing Around With Margins In CSS (2:20)
(Prerequisite) Introduction to JavaScript
01. Course Requirements (4:44)
02. HTML, CSS And Javascript Crash Course (4:53)
03. Adding In Functions (4:35)
04. Scaling Functions (4:27)
05. Changing The Text In Javascript (4:50)
06. Variables (5:40)
07. Arrays (5:30)
08. Objects (6:36)
09. Variable Scope (5:04)
10. Adding User Input Text (5:05)
11. Calling Functions (3:56)
12. If Statements (4:49)
13. Else If And Else Statements (4:05)
14. Changing The Style With Javascript (5:49)
TensorFlow JS Fundamentals
01. What Is Machine Learning (6:41)
02. What Is Tensorflow JS (4:29)
03. Load Tensorflow Object (5:08)
Source Files
01d Build Your First Tensors
01. Linear Algebra For Machine Learning (4:46)
02. Build Tensors (13:35)
03. Tensor Utility Methods (9:14)
04. Perform Math With Tensors (9:57)
Source Files
What is a Neural Network
01. What Is Deep Learning (6:10)
02. What Is A Neural Network (8:08)
Source Files
Build a Neural Network with One Hot Encoding
01. What Is One Hot Encoding (6:52)
02. Build Training Data (7:34)
03. Build The Neural Network (6:48)
04. Train The Neural Network (9:33)
05. Make A Prediction (10:11)
Source Files
Build a Neural Network to Detect Lines in Images
01. Build Training Data To Represent Images (12:15)
02. Build The Convolutional Neural Network (10:39)
03. Train The Convolutional Neural Network (9:06)
04. Make A Prediction Of Number Of Lines (15:05)
Source Files
Build an LSTM Recurrent Neural Network
01. What Is A Recurrent Neural Network (6:38)
02. Generate Sequence And Label (6:25)
03. Generate Dataset (6:02)
04. Build The LSTM Model (4:55)
05. Train The Model (11:25)
Source Files
Build a Model to Classify Iris Species
01. Process Iris Data (7:37)
02. Convert Data To Tensors (8:45)
03. Separate Training And Testing Data (8:54)
04. Create Training And Testing Datasets (4:42)
05. Build The Model (9:29)
06. Train The Model (4:10)
07. Make A Prediction (8:45)
Source Files
Build a Positive vs Negative Text Classifier
01. Load Model And Dataset (5:57)
02. Get User Input For Sentiment Analysis (10:59)
03. Make A Prediction (7:11)
Source Files
Build a Neural Network to Recognize Handwriting
01. What Is A Convolutional Neural Network (19:29)
02. Set Up Canvas To Load Image Data (10:35)
03. Load Mnist Dataset (6:47)
04. Separate Training And Testing Data (5:40)
05. Build The Model (6:48)
06. What Are The Network's Layers (14:14)
07. Train The Model (11:27)
08. Create Training Batches (6:14)
09. Create Testing Batches (11:31)
10. Fit Neural Network Through Data (8:54)
Source Files
10. Fit Neural Network Through Data
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