Machine Learning

Making sense of ML

CNN Explainer (link)
Interpretable Machine Learning (link)
Physics-based Deep Learning Book (link)
Mathematics For Machine Learning (link) (GitHub)
SHAP and LIME Python Libraries (Part 1) (Part 2) (SHAP in Chinese)
- Limitations of SHAP (1, 2, 3)

Deep Learning Tuning Playbook - Google Research (link)
Bayesian Optimization for Hyperparameter Tuning (link)
Hyperparameter tuning tools: (Tune) (scikit-optimize)(SHERPA)
- How to tune Pytorch Lightning hyperparameters
NNI (Neural Network Intelligence, link): a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture Search, Hyperparameter Tuning and Model Compression
Why One-Hot Encode Data in Machine Learning? (link)

Data-Driven Science and Engineering - UW (link)
Educational Resources for AI and Machine Learning by AI2ES (link)
- AI4ESS by NCAR (link) (YouTube) (GitHub)
- Trustworthy Artificial Intelligence for Environmental Science (TAI4ES) Summer School 2021 (link) (Recording & Slides)
- TAI4ES 2022 Summer School (link) (Recordings)
Machine Learning and Deep Learning for Environmental and Geosciences -- AGU Tutorial (link)
Machine Learning in Python for Environmental Science Problems -- AMS Tutorial (link)
Deep Learning (MIT ebook)(Online with code)
Reinforcement Learning and Sequential Decision Problems -- Prof. Warren Powell (link)
Reinforcement Learning Knowledge (in Chinese)
Probabilistic Machine Learning (link)
Machine Learning A-Z (link)