03 Visualize Training | Mammoth Interactive

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AI Art Revolution - Train Neural Networks to Create Masterful Illustrations with Python

Machine Learning Fundamentals

01 Project Preview (3:34)
02 Project 2 Preview (1:06)
03 Project 3 Overview (0:47)
04 What You-ll Need (8:09)
Source Files

Collect and Process Data

01 Load Drawings Dataset (20:06)
02 Label Data (12:17)
03 Build A Training Dataset (8:30)
04 Visualize Dataset (6:20)
05 Batch And Shuffle Data (4:39)
Source Files

Build a Generative Neural Network

01 Build A Generator (13:46)
02 Generate Noise (11:22)
Source Files

Generative Neural Network Fundamentals

01 What Is A Generative Neural Network (7:26)
02 What Is A Convolutional Neural Network (7:04)
03 How To Build A Convolutional Neural Network (14:04)
04 How To Build A Dense Layer (10:48)
05 How To Build A Batch Normalization Layer (5:36)
06 Leaky Relu Activation Function (6:04)
07 Transposed Convolution Layer (10:34)
08 Hyperbolic Tangent (Tanh) Activation Function (2:59)
Source Files

Build a Discriminator Neural Network

01 How Do You Build A Discriminator (10:19)
02 Build A Discriminator (10:53)
Source Files

Evaluate the Model's Performance

01 Performance Of A Machine Learning Algorithm (4:14)
02 Calculate Loss (7:11)
03 What Is The Adam Optimizer (6:55)
04 Assign Optimizers (3:02)
Source Files

Train the Model to Draw

01 Build A Training Step (11:03)
02 Train The Model (6:54)
03 Visualize Training (29:10)
Source Files

Test the Model's Drawing Ability

01 Test The Model (9:22)
Source Files

03 Visualize Training

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