It starts with probability and linear algebra, and gradually builds up to the common notation and techniques used in modern research papers – focusing on ...

This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data ...

This book is meant for use with a self-contained course that introduces many basic principles and techniques needed for modern data analysis.

This book is meant for use with a self-contained course that introduces many of the basic mathematical principles and techniques needed for modern data ...

Probability and Linear Algebra are essential foundations for much of data analysis, and hence also in this book. This text includes reviews of these topics.

It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and ...

It encompasses a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and ...

Mathematical foundations of data analysis · Graphs and the Laplace matrix · The spectrum of a graph · Markov processes in networks · Centrality measures.

58,66 $ It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and ...

It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and ...