Название: Foundations of Data Science Автор: Avrim Blum, John Hopcroft, Ravi Kannan Издательство: Cambridge University Press Год: 2020 Формат: PDF Страниц: 432 Размер: 11 Mb Язык: English
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.
Mining of Massive Datasets Название: Mining of Massive Datasets Автор: Leskovec J., Rajaraman A., Ullman J.D. Издательство: Stanford University Год: 2019 Формат: pdf Страниц:...
Introduction to Statistical Relational Learning Название: Introduction to Statistical Relational Learning Автор: Lise Getoor and Ben Taskar Издательство: The MIT Press Год: 2007 Формат: PDF Размер:...
Graph-Based Social Media Analysis Название: Graph-Based Social Media Analysis Автор: Ioannis Pitas Издательство: CRC Press Год: 2015 Формат: PDF Размер: 25 Мб Язык: английский /...
Навигация
Вход на сайт
Реклама
Foundations of Data Science 
