Mathematical Introduction To Data Science

[Farid-Khan]

English | 2024 | ISBN: 978-3-662-69426-8 | 301 pages | True PDF | 3.58 MB​

Introduction to Data Science (Laura Igual) (2017)
Catergory: Computer Technology, Nonfiction
Publisher: Springer International Publishing

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.

Contents of Download:
Mathematical Introduction To Data Science.pdf (Laura Igual) (2017) (3.59 MB)

️ Mathematical Introduction To Data Science (3.59 MB)

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