A repository to share tutorials for learning machine learning methods in Python (don't waste your time with R; it is best suited to academia).
Rule generation is a common task in the mining of frequent patterns. An association rule is an implication expression of the form X→Y, where X and Y are disjoint itemsets. A more concrete example based on consumer behaviour would be {Diapers}→{Beer} suggesting that people who buy diapers are also likely to buy beer. Association Rules in {mlxtend}
Principal Component Analysis (PCA) is fundamentally a dimensionality reduction algorithm, but it can also be useful as a tool for visualization, for noise filtering, for feature extraction and engineering, and much more. PCA Tutorial in {sklearn}