A collection of learning resources for curious software engineers
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A collection of learning resources for curious software engineers
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Summer 2027 software engineering, data science, AI, quant, product management, and hardware internship postings. Updated daily by Simplify and Pitt CSC.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Best Practices on Recommendation Systems
Turns Data and AI algorithms into production-ready web applications in no time.
Low-code framework for building custom LLMs, neural networks, and other AI models
Open Machine Learning Course
🔩 Like builtins, but boltons. 250+ constructs, recipes, and snippets which extend (and rely on nothing but) the Python standard library. Nothing like Michael Bolton.
A curated list of community detection research papers with implementations.
A curated list of data mining papers about fraud detection.
Math & CS awesome List, distinguished by proof and logic technique
Don't memorize ML. Understand it from first principles including Inference, Cuda, Deep Learning, Data Science and Reinforcement Learning
Python-based implementations of algorithms for learning on imbalanced data.
A fast xgboost feature selection algorithm