Book Details
Format
Paperback / Softback
ISBN-10
3662694255
ISBN-13
9783662694251
Edition
2024 ed.
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Aug 31st, 2024
Print length
299 Pages
Weight
538 grams
Dimensions
23.30 x 15.60 x 1.80 cms
Product Classification:
DatabasesDatabases / Data managementMaths for computer scientists
Ksh 13,500.00
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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.
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.
Get Mathematical Introduction to Data Science by at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG and it has pages.
