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This course explains how convolutional neural networks extract features from images and demonstrates image preprocessing, CNN construction, training, and inference with Python and PyTorch.
Syllabus
Intro
What Makes a Convolutional Neural Network
Image preprocessing for CNNs
Common components of a CNN
Components: pooling layers
Building the CNN with PyTorch
Notable CNNs
Implementation of CNNs
Image Preprocessing for CNNs
How to normalize images for CNN input
Image preprocessing pipeline with pytorch
Pytorch data loading pipeline for CNNs
Building the CNN with PyTorch
CNN training parameters
CNN training loop
Using PyTorch CNN for inference
Taught by
James Briggs