- Microsoft’s Recommenders Repository – “provides examples and best practices for building recommendation systems, provided as Jupyter notebooks.”
- Ben E. C. Boyter. Processing 40 TB of Code from ~10 Million Projects with a Dedicated Server and Go for $100.
- Tristan Greene. 2010-2019: The Rise of Deep Learning. thenextweb, 2020.
- Nathan Piccini. 101 Machine Learning Algorithms for Data Science with Cheatsheets. datasciencedojo, 2019.
- Cecelia Shao. If You’re a Developer Transitioning into Data Science, Here are Your Best Resources. freecodecamp, 2019.
- Towards Data Science – Offers numerous articles on data science related topics.
- The Open source Data Science Masters – Gathers some of the best resources from around the web to create a curriculum in data science.
- Machine Learning Notebooks.*
- Uber’s Ludwig – “a toolbox that allows [one] to train and test deep learning models without the need to write code.”