Avrim Blum , John Hopcroft , Ravindran Kannan Additional Author mixed material bibliography Islamabad Al Hafiz Traders 2020 en English

Book

432 This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data Avrim Blum , John Hopcroft , Ravindran Kannan Computer Science Data Science 1. Computer Science 2. Software Engineering 3. Dat Data Science Information Technology 006..312 9781108485067 NUML LIBRARY RAWALPINDI (National University of Modern Languages) NUML library is the state of art which equipped “RESEARCH FACILITATION CENTRE” with latest computers for readers to access the digital library of more than 23000 research journals and 130000 online books and E-Library of NUML-Rawalpindi. 006..312 14207 14207.jpg.jpg 21459 2025-09-04 18:32:53 2026-02-03 16:53:52 machine generated