Master Data Prediction, Recognition, Classification and Search Algorithms with Python and TensorFlow
Become an expert in building dynamic Python machine learning models with TensorFlow!
This in-depth course takes you on a journey through the essentials of TensorFlow, teaching you how to create sophisticated models that are capable of adapting and evolving.
You'll start with the basics of TensorFlow and progress to advanced techniques, including recurrent and convolutional neural networks.
With hands-on projects and challenging real-world problems, you'll cement your understanding and sharpen your skills.
Whether you're just starting out or already have experience, this course will elevate your TensorFlow expertise, giving you the confidence to tackle even the most complex machine learning challenges.
Your Instructor
This course is a collaborative effort between multiple Mammoth Instructors.
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 13 years, Mammoth Interactive has built a global student community with 6+ 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 Course Intro (6:10)
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Start01 Intro to Tensorflow (5:33)
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Start02 Installing Tensorflow (3:52)
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Start03 Intro to Linear Regression (9:26)
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Start04 Linear Regression Model - Creating Dataset (5:49)
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Start05 Linear Regression Model - Building the Model (7:22)
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Start06 Linear Regression Model - Creating a Loss Function (5:57)
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Start07 Linear Regression Model - Training the Model (12:42)
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Start08 Linear Regression Model - Testing the Model (5:22)
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Start09 Summary and Outro (2:55)
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StartSource Files
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Start00 Course Intro (6:57)
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Start01 Intro To Image Recognition (14:07)
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Start02 Intro To MNIST (4:43)
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Start03 Building A CNN Part 1 - Obtaining Data (15:40)
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Start04 Building A CNN Part 2 - Building The Model (10:14)
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Start05 Building A CNN Part 3 - Adding Loss And Optimizer Functions (4:57)
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Start06 Building A CNN Part 4 - Train And Test Functions (10:58)
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Start07 Building A CNN Part 5 - Train And Test The Mode (9:17)
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Start08 MNIST Image Recognition With Keras Sequential Model (13:24)
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Start09 Summary And Outro (3:40)
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StartSource Files