Introduction to Deep Learning · HIT

Week 8   Part III · Architectures & Representation Learning

Convolutional Networks I

Convolution, pooling, and feature maps; building a CNN image classifier.

Curated, free, canonical references for this week: a course or lecture, a book chapter, a video, and an authoritative blog post or official tutorial. Each opens in a new tab.

Course
Stanford CS231n: Deep Learning for Computer Vision cs231n.github.io

The canonical CNN course, from convolution and pooling through full image-classifier architectures.

Book
Dive into Deep Learning, Chapter 7: Convolutional Neural Networks d2l.ai

Free PyTorch chapter on convolutions, pooling, receptive fields, and building LeNet.

Video
CS231n Lecture 5: Convolutional Neural Networks youtube.com

Focused lecture introducing convolution, filters/feature maps, and pooling.

Blog / Docs
CS231n Notes: Convolutional Networks cs231n.github.io

Authoritative notes on conv layers, stride/padding, pooling, and activation maps with formulas.

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