Data Science Cheat Sheet (Datacamp) The datacamp cheat sheets are always worth a look. However, I would recommend this cheat sheet only for absolute beginners in the field of data science. If you focus on learning core machine learning concepts and you already have some experience, please skip this cheat sheet. Eventually, I compiled over 20 Machine Learning-related cheat sheets. Some I reference frequently and thought others may benefit from them too. This post contains 27 of the better cheat sheets I. There are several areas of data mining and machine learning that will be covered in this cheat-sheet: Predictive Modelling. Regression and classification algorithms for supervised learning (prediction), metrics for evaluating model performance.
Cheat sheets for machine learning are plentiful. Quality, concise technical cheat sheets, on the other hand... not so much. A good set of resources covering theoretical machine learning concepts would be invaluable.
Shervine Amidi, graduate student at Stanford, and Afshine Amidi, of MIT and Uber, have created just such a set of resources. The VIP cheat sheets, as Shervine and Afshine have dubbed them (Github repo with PDFs available here), are structured around covering key top-level topics in Stanford's CS 229 Machine Learning course, including:
- Notation and general concepts
- Linear models
- Classification
- Clustering
- Neural networks
- ... and much more
Links to individual cheat sheets are below:
Data Science Models Cheat Sheet Answers
You can visit Shervine's CS 229 resource page or the Github repo for more information, or can download the cheat sheets from the direct download links above.
You can also find all of the sheets bundled together into a single 'super VIP cheat sheet.'
Data Camp Cheat Sheet
Thanks to Shervine and Afshine for putting these fantastic resources together.
Data Science Models Cheat Sheet 2019
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