awesome-online-machine-learning
github.com/online-ml/awesome-online-machine-learning ↗:bookmark_tabs: Online machine learning resources
626
GitHub Stars
107
Curated Resources
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Courses and booksBlog postsSoftwarePapers
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Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me miscellaneous resources from awesome-online-machine-learning"
Installation instructions →What's inside
Papers
- A Complete Recipe for Stochastic Gradient MCMC (2015)Miscellaneous
- Adaptive Regularization of Weight Vectors (2009)Linear models
- Ad Click Prediction: a View from the Trenches (2013)Linear models
- A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Ensemble models
- A globally optimal fast iterative linear maximum likelihood classifier (2023)Linear models
- AMF: Aggregated Mondrian Forests for Online Learning (2019)Decision trees
Courses and books
Blog posts
- Anomalies detection using River (Matias Aravena Gamboa, 2021)
- Anomaly Detection with Bytewax & Redpanda (Bytewax, 2022)
- Fennel AI blog posts about online recsys
- Introdução (não-extensiva) a Online Machine Learning (Saulo Mastelini, 2021)
- Machine learning is going real-time (Chip Huyen, 2020)
- Real-time machine learning: challenges and solutions (Chip Huyen, 2022)
Showing a sample of 107 resources. View the full list on GitHub →