Statistical Learning
Showing 9 of 9 projects
A curated collection of must-use resources for AI engineering, including books, courses, papers, frameworks, and tools.
A curated list of must-use resources for AI engineering, including books, courses, papers, frameworks, and tools.
A comprehensive collection of tutorials, examples, and resources for understanding and solving machine learning and pattern classification problems.
Transpile trained machine learning models into native code (Java, C, Python, Go, etc.) with zero dependencies.
A fast, ergonomic machine learning library for Rust with broad algorithm coverage and WASM-first defaults.
A Python library for statistical learning with a focus on time-dependent modeling, including point processes and generalized linear models.
A TypeScript machine learning library for the web and Node.js with a simple, consistent API.
Jupyter notebooks implementing algorithms, proofs, and summaries from 'The Elements of Statistical Learning' textbook.
An R package for automatic optimal predictor ensembling via cross-validation with dozens of machine learning algorithms.
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.