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Understanding UMAP - Google PAIR

Has nice interactive examples and UMAP vs t-SNE

Learn Machine Learning @sh.itjust.works
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MIT OpenCourseWare: Introduction To Machine Learning

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

Style Guide for Python Code: PEP 8

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

MIT OpenCourseWare: Statistical Learning Theory

Learn Machine Learning @sh.itjust.works
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MIT OpenCourseWare: Mathematics Of Machine Learning

Broadly speaking, Machine Learning refers to the automated identification of patterns in data. As such it has been a fertile ground for new statistical and algorithmic developments. The purpose of this course is to provide a mathematically rigorous introduction to these developments with emphasis on methods and their analysis.

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

Durham University Materials for COMP3547 (Deep Learning) and COMP3667 (Reinforcement Learning) from Dr. Robert Lieck

Includes lectures, lecture notes and assignments.

Lectures for Deep Learning: https://www.youtube.com/playlist?list=PLMsTLcO6etti_SObSLvk9ZNvoS_0yia57

Lectures for Reinforcement Learning: https://www.youtube.com/playlist?list=PLMsTLcO6ettgmyLVrcPvFLYi2Rs-R4JOE

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

Rules of Machine Learning from Google

A good set of best practices for deployment that isn't language-specific

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

Coding Practices for Python/ML

Coding nowadays is a big part of ML and while it's important that the model works well, it's also important that the code is written properly too.

Link is the general python version, ML-specific version here: https://github.com/davified/clean-code-ml

Video version: https://bit.ly/2yGDyqT

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

Tutorial: Image Recognition with CNN in Matlab

Introduces neural networks, the convolution operation, a few critical machine learning concepts and some state-of-the-art CNN models. Includes a hands-on Matlab tutorial (and code) demonstrating the model configuration, training process, and performance evaluation using the MNIST dataset.

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

Tutorial: State of Charge Estimation with EKF and SVSF in Matlab

This tutorial describes the process for the state of charge (SOC) estimation of Li-Ion cells using an equivalent circuit model. It helps students create and run a SOC estimation strategy based on the 3rd-order R-RC model in MATLAB-Simulink. The tutorial starts with a general overview of state estimation using the extended Kalman filter (EKF) and the novel smooth variable structure filter (SVSF) method.

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

Standford University Cheat Sheets for ML (web version)

I'm not sure if I'd call a 10+ page pdf a "cheat sheet" but they are good resources

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

Materials from CORNELL CS4780/CS5780: Machine Learning for Intelligent Systems

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

Good collection of introductions to topics for stats and machine learning: Nature Methods' Points of Significance

From Nature.com - Statistics for Biologists. A series of short articles that are a nice introduction to several topics and because the audience is biologists, the articles are light on math/equations.

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

Deep learning: the unintuitive relationship between overparameterization, overfitting and generalization

See also: the phenomenon of double descent.

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What's the kernel trick? (explanation)

eranraviv.com What is the Kernel Trick?

Every so often I read about the kernel trick. Each time I read about it I need to relearn what it is. Now I am thinking "Eran, don't you have this fancy bl

A nice visualization/example of the kernel trick. A more mathematical explanation can be found here.

Learn Machine Learning @sh.itjust.works
ShadowAether @sh.itjust.works

A good introduction/overview to neural network theory: Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville (Free, online copy)

I found this book a very good reference when learning about autoencoders