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aideep-diveReading CMU 07-280 AI & ML I

Encoding Image Structure with Convolutional Networks | CMU 07-280 Lecture 14

Lecture 14 replaces dense image models with local connectivity and parameter sharing, moving from convolution, stride, padding, and pooling to AlexNet, GPU data parallelism, ResNet skip connections, and BatchNorm.

#cmu#ai-course#computer-vision#cnn#alexnet
aideep-diveReading CMU 07-280 AI & ML I

Stage Review II: Building AlexNet and GPT-2 as Working Systems | CMU 07-280 Topic Guide

Stage II uses HW8 and HW11 to test whether representation, computation graphs, training, transfer, and generation actually connect, rather than treating CNNs and Transformers as diagrams to memorize.

#cmu#ai-course#alexnet#gpt-2#deep-learning