University of Michigan - Ann Arbor

- Supervised statistical learning
- Unsupervised statistical learning
- Time series learning
- Semi-Supervised learning

Types of statistical learning

Machine Learning Yearning, a free ebook from Andrew Ng, teaches you how to structure Machine Learning projects.
https://www.deeplearning.ai/machine-learning-yearning/

Note: The content of the book is aligned with the Coursera Deeplearning.ai specialization.  https://www.deeplearning.ai/deep-learning-specialization/ 

Machine Learning Yearning (Deeplearning.ai)

Unsupervised machine learning methods find structure in unlabeled data.
They are used when we DON'T have prior knowledge about the categories.

Unsupervised statistical learning

Supervised machine learning methods predict target/output values after getting trained on example pairs of labeled data.

We can use these methods only when we have some prior knowledge about the categories or the values that we are interested in predicting or estimating.

Supervised statistical learning

A time series is defined as a collection of random variables indexed according to the order they are obtained in time. The primary objective of time series analysis is to develop mathematical models that provide plausible descriptions for data.

Time series

Semi-supervised learning lies somewhere between supervised and unsupervised learning. It takes small amount of labeled data to start learning and then moves on to huge quantity of unlabaled data to develop further.

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