Overview
Syllabus
How Convolution Works.
The Softmax neural network layer.
Batch normalization.
Build a 2D convolutional neural network, part 1: Getting started.
Build a 2D convolutional neural network, part 2: Overview.
Build a 2D convolutional neural network, part 3: MNIST digits.
Build a 2D convolutional neural network, part 4: Model overview.
Build a 2D convolutional neural network, part 5: Pre-trained model results.
Build a 2D convolutional neural network, part 6: Examples of successes and failures.
Build a 2D convolutional neural network, part 7: Why Cottonwood?.
Build a 2D convolutional neural network, part 8: Training code setup.
Build a 2D convolutional neural network, part 9: Adding layers.
Build a 2D convolutional neural network, part 10: Connecting layers.
Build a 2D convolutional neural network, part 11: The training loop.
Build a 2D convolutional neural network, part 12: Testing loop.
Build a 2D convolutional neural network, part 13: Loss history and text summary.
Build a 2D convolutional neural network, part 14: Collecting examples.
Build a 2D convolutional neural network, part 15: Rendering examples.
Build a 2D convolutional neural network, part 16: Cottonwood code tour.
Build a 2D convolutional neural network, part 17: Cottonwood cheatsheet.
Taught by
Brandon Rohrer