There are lots of cheat sheets out there of varying quality covering vastly different topics which are all considered to be under the "data science" banner. Some are great, some are good, many are not worth your time. Occasionally a gem can be found, covering some particular niche to some acceptable level of understanding.
This is where the recent "Data Science Cheatsheet" by Maverick Lin comes in. It is a relatively broad undertaking at a novice depth of understanding, but it does what it does very well. The 9 page treatment concisely covers such diverse aspects of data science as:
- stats & probability
- data preparation
- feature engineering
- machine learning
- deep learning
- ...and much more
It's worth stressing that this would not be much immediate value to seasoned veterans of data science, but beginners are encouraged to check it out, as are those brushing up for an interview or just looking for some light refresher reading.
You can visit the Github repo for more information, or can download the cheat sheet from this direct download link.
Thanks to Maverick Lin for putting this cheat sheet together, which is an evolving work in progress.
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