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portada Mathematical Introduction to Data Science
Type
Physical Book
Publisher
Author
Language
English
Pages
299
Format
Paperback
ISBN13
9783662694251
Edition No.
2024th

Mathematical Introduction to Data Science

Sven A. Wegner (Author) · Springer · Paperback

Mathematical Introduction to Data Science - Sven A. Wegner

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Synopsis "Mathematical Introduction to Data Science"

This textbook is intended for students of mathematics who have completed the foundational courses of their undergraduate studies and now want to specialize in Data Science and Machine Learning. It introduces the reader to the most important topics in the latter areas focusing on rigorous proofs and a systematic understanding of the underlying ideas. The textbook comes with 121 classroom-tested exercises. Topics covered include k-nearest neighbors, linear and logistic regression, clustering, best-fit subspaces, principal component analysis, dimensionality reduction, collaborative filtering, perceptron, support vector machines, the kernel method, gradient descent and neural networks.

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