This is a draft cheat sheet. It is a work in progress and is not finished yet.
Basic terms
regression |
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
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