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Machine Learning Basics Cheat Sheet (DRAFT) by

This is a draft cheat sheet. It is a work in progress and is not finished yet.

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Basic terms

predicting a value based on known historical data
Giving the machine some data, it will find hidden patterns and predict results.
How to collect data: manually and automa­tic­ally.
Features: parameters or variables, the factors for a machine to look at.
Algori­thms: Any problem can be solved differ­ently. The method you choose affects the precision, perfor­mance, and size of the final model.

Three components of machine learning

Learning vs Intell­igence

Artificial intell­igence is the name of a whole knowledge field, similar to biology or chemistry.
Machine Learning is a part of artificial intell­igence. An important part, but not the only one.
Neural Networks are one of machine learning types. A popular one, but there are other good guys in the class.
Deep Learning is a modern method of building, training, and using neural networks. Basically, it's a new archit­ecture. Nowadays in practice, no one separates deep learning from the "­ord­inary networ­ks". We even use the same libraries for them.


Classical Machine Learning