ENGLISH

Mathematical Introduction to Data Science

Book information

Publisher
Springer
Year
2024
ISBN
3662694255, 9783662694251
Language
english
Format
PDF
Filesize
3 MB (3042094 bytes)
Edition
2024
Pages
308\301
Time added
2024-12-02 09:41:31

Description

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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