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 iclr-blogposts.github.io
How to compute Hessian-vector products? | ICLR Blogposts 2024
| | jingnanshi.com
Automatic Differentiation: Forward and Reverse
2.7 parsecs away

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| | Tutorial on automatic differentiation
| | bytepawn.com
Bytepawn - Marton Trencseni - PyTorch Basics: Solving the Ax=b matrix equation with gradient descent
3.9 parsecs away

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| | I will show how to solve the standard A x = b matrix equation with PyTorch. This is a good toy problem to show some guts of the framework without involving neural networks.
| | liorsinai.github.io
MicroGrad.jl: Part 1 ChainRules - Lior Sinai
2.9 parsecs away

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| | A series on automatic differentiation in Julia. Part 1 provides an overview and defines explicit chain rules.
| | wtfleming.github.io
Cats vs Dogs - Part 2 - 98.6% Accuracy - Binary Image Classification with Keras and Transfer Learning
11.6 parsecs away

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| [AI summary] This article demonstrates how to achieve 98.6% accuracy in binary image classification of cats and dogs using Keras and transfer learning with the VGG16 model.