inside front cover

Core algorithms inside the book

Algorithm	Use case	First introduced
K-means	Clustering	Section 10
DBSCAN	Clustering	Section 10
Jaccard similarity computation	Text comparison	Section 13
Cosine similarity computation	Text comparison	Section 13
Principal component analysis	Dimension reduction	Section 14
Singular value decomposition	Dimension reduction	Section 14
Power iteration	Eigenvector computation	Section 14
TFIDF vectorization	Text comparison	Section 15
Shortest path length computation	Network path optimization	Section 18
PageRank	Network centrality measurement	Section 19
Markov clustering	Social network clustering	Section 19
K-nearest neighbors	Supervised classification	Section 20
Cross-validation	Model performance testing	Section 20
Perceptron	Supervised classification	Section 21
Linear regression	Supervised classification	Section 21
Decision tree	Supervised classification	Section 22
Random forest	Supervised classification	Section 22