Here is a great set of cheat sheet on some of the following topics:
- Supervised learning
- Unsupervised learning
- Deep learning
- Probability and statistics
- Linear algebra
- Tips and tricks including performance metrics
https://stanford.edu/~shervine/teaching/cs-229/
Hope you liked the cheat sheets on different topics of machine learning and data science.
Ajitesh Kumar
Ajitesh has been recently working in the area of AI and machine learning. Currently, his research area includes Safe & Quality AI. In addition, he is also passionate about various different technologies including programming languages such as Java/JEE, Javascript and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc.
He has also authored the book, Building Web Apps with Spring 5 and Angular.
He has also authored the book, Building Web Apps with Spring 5 and Angular.
Latest posts by Ajitesh Kumar (see all)
- Unit Tests & Data Coverage for Machine Learning Models - May 11, 2019
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- Machine Learning Cheat sheet (Stanford) - March 23, 2019
