Unsupervised Machine Learning (UML) intro

This tutorial will provide a hands-on intro to core techniques of unsupervised learning. We will cover, data preprocessing, PCA, NMF, UMAP, K-means and methods of interpreting results of their application.

Notebook(s)

• Hands-on Intro to Dimensionality reduction and Clustering

Recommended Datacamp exercises:

• Python

Recommended Readings and resources

• Python Data Science Handbook Chapter 5

  • What Is Machine Learning?
  • Introducing Scikit-Learn
  • Feature Engineering
  • In Depth: Principal Component Analysis
  • In Depth: k-Means Clustering

• Implementation tutorials on YT PCA and K-means from this list