ethz_cs_summaries
stanford-cs-229-machine-learning
ethz_cs_summaries | stanford-cs-229-machine-learning | |
---|---|---|
2 | 1 | |
130 | 17,045 | |
- | - | |
0.0 | 0.0 | |
over 2 years ago | about 4 years ago | |
- | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ethz_cs_summaries
stanford-cs-229-machine-learning
What are some alternatives?
eth-cs-notes - Lecture notes and cheatsheets for Master's in Computer Science at ETH Zurich
machine-learning-roadmap - A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
Data-science-best-resources - Carefully curated resource links for data science in one place
applied-ml - 📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
ETH_room_viewer - Room finding tool for ETH
modern-php-cheatsheet - Cheatsheet for some PHP knowledge you will frequently encounter in modern projects.
Data-Science-Roadmap - Data Science Roadmap from A to Z
fsharp-cheatsheet - An updated cheat sheet for F# 🔷🦔💙💛🤍💚
mongodb-cheatsheet - Kick start with mongodb
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
MoneroAddressesCS - An infographic about Monero Keys and Addresses, their relations and scopes
Awesome-VAEs - A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.