- Curated list of many resources for learning ML https://sgfin.github.io/learning-resources/ 18 comments learnmachinelearning
- One-stop Source: ML Resources https://sgfin.github.io/learning-resources/ 3 comments datascience
Linked pages
- fast.ai – fast.ai—Making neural nets uncool again https://fast.ai 382 comments
- http://www.tug.org/texshowcase/cheat.pdf 271 comments
- The Matrix Calculus You Need For Deep Learning https://explained.ai/matrix-calculus/ 242 comments
- Practical Deep Learning for Coders - Practical Deep Learning https://course.fast.ai 177 comments
- Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares http://vmls-book.stanford.edu/ 124 comments
- The Modern Algorithmic Toolbox (CS168), Spring 2023 https://web.stanford.edu/class/cs168/index.html 103 comments
- Mathematics for Machine Learning | Companion webpage to the book “Mathematics for Machine Learning”. Copyright 2020 by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. Published by Cambridge University Press. https://mml-book.github.io/ 81 comments
- Deep Learning http://www.deeplearningbook.org/ 79 comments
- Feature Visualization https://distill.pub/2017/feature-visualization/ 77 comments
- Visual Information Theory -- colah's blog https://colah.github.io/posts/2015-09-Visual-Information/ 72 comments
- Measure, Integration & Real Analysis http://measure.axler.net/ 72 comments
- Understanding LSTM Networks -- colah's blog https://colah.github.io/posts/2015-08-Understanding-LSTMs/ 64 comments
- https://web.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf 56 comments
- Learn R, Python & Data Science Online | DataCamp https://datacamp.com 51 comments
- Common statistical tests are linear models (or: how to teach stats) https://lindeloev.github.io/tests-as-linear/ 46 comments
- Learning From Data - Online Course (MOOC) https://work.caltech.edu/telecourse.html 46 comments
- Causal Inference: What If (the book) | Miguel Hernan's Faculty Website | Harvard T.H. Chan School of Public Health https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/ 42 comments
- Transformers from scratch | peterbloem.nl http://peterbloem.nl/blog/transformers 40 comments
- [1802.01528] The Matrix Calculus You Need For Deep Learning https://arxiv.org/abs/1802.01528 40 comments
- A Recipe for Training Neural Networks http://karpathy.github.io/2019/04/25/recipe/#2-set-up-the-end-to-end-trainingevaluation-skeleton--get-dumb-baselines 39 comments
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