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Teaching Neural Networks to Illustrate: A Complete Guide to Training Python-Based AI for Drawing
Mammoth Interactive Courses Introduction
Preface
00 About Mammoth Interactive (1:12)
01 How To Learn Online Effectively (13:46)
Source Files
Machine Learning Fundamentals
Project Preview (1:47)
Project 2 Preview (1:06)
Project 3 Overview (0:47)
What You-ll Need (2:43)
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Collect and Process Data
Load Drawings Dataset (10:03)
Label Data (12:17)
Build A Training Dataset (8:30)
Visualize Dataset (6:20)
Batch And Shuffle Data (4:39)
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Build a Generative Neural Network
Build A Generator (13:46)
Generate Noise (5:41)
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Generative Neural Network Fundamentals
What Is A Generative Neural Network (7:26)
What Is A Convolutional Neural Network (7:04)
How To Build A Convolutional Neural Network (14:04)
How To Build A Dense Layer (2:42)
How To Build A Batch Normalization Layer (1:52)
Leaky Relu Activation Function (6:04)
Transposed Convolution Layer (5:17)
Hyperbolic Tangent (Tanh) Activation Function (2:59)
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Build a Discriminator Neural Network
How Do You Build A Discriminator (10:19)
Build A Discriminator (10:53)
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Evaluate the Model's Performance
Performance Of A Machine Learning Algorithm (4:14)
Calculate Loss (7:11)
What Is The Adam Optimizer (6:55)
Assign Optimizers (3:02)
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Train the Model to Draw
Build A Training Step (11:03)
Train The Model (6:54)
Visualize Training (14:35)
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Test the Model's Drawing Ability
Test The Model (9:22)
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How Do You Build A Discriminator
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