30 Papers
A curated reading list of 30 foundational AI and deep learning papers, hosted in full with plain-language explanations so beginners can work through the classics.
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Self Driving Cars Are Fun!
A student's write-up of building a self-driving car autopilot in Keras, walking through training a neural network to ste…
Analyzing 50k Fonts Using Deep Neural Networks
Erik Bernhardsson scrapes 50,000 fonts and trains neural networks on them, then explores the learned font space with vis…
Stanford CS224d
Course site for Stanford's deep learning for natural language processing class, with lecture slides, notes, and assignme…
Deep Learning Training vs. Inference
An explainer on how AI models are trained and then put to work, covering the difference between deep learning training a…
Justin Pinkney
A personal site of experiments and write-ups on generative art and deep learning, including projects that combine the tw…
Graph Convolutional Networks
An introduction by Thomas Kipf to neural networks on graph-structured data such as social and citation networks, explain…
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