This book focuses on dealing with large-scale data, a field commonly referred to as data mining. The book is divided …
This book describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal …
Two features of "Processing Random Data" differentiate it from other similar books: the focus on computing the reproducibility error for …
Designed as a textbook for a one or two-term introduction to mathematical statistics for students training to become data scientists, …
Written for those who need an introduction,Applied Time Series Analysisreviews applications of the popular econometric analysis technique across disciplines. Carefully …
Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of …
Visualizing the data is an essential part of any data analysis. Modern computing developments have led to big improvements in …
Why study the theory of experiment design? Although it can be useful to know about special designs for specific purposes, …
Statistics is a thought process. In this comprehensive introduction to statistical methods and data analysis, the process is presented utilizing …
Ott and Longnecker's AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Sixth Edition, provides a broad overview of statistical methods …
This book introduces the topics of Big Data, data analytics and data science and features the use of open source …
Cover ; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: How to Sound …
Principles and Methods for Data Science, Volume 43 in the Handbook of Statistics series, highlights new advances in the field, …
The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data …
Ten years ago Bill Gale of AT&T Bell Laboratories was primary organizer of the first Workshop on Artificial Intelligence and …
Providing the knowledge and practical experience to begin analysing scientific data, this book is ideal for physical sciences students wishing …
An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data.Analyzing …
This is an introduction to time series that emphasizes methods and analysis of data sets. The logic and tools of …
This comprehensive text introduces readers to the most commonly used multivariate techniques at an introductory, non-technical level. By focusing on …
The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings …
This textbook provides an easy-to-understand introduction to the mathematical concepts and algorithms at the foundation of Data Science. It covers …
"Introduction to Applied Bayesian Statistics and Estimation for Social Scientists' covers the complete process of Bayesian statistical analysis in great …
Dr. Scott Lynch has made a great job for those (like me) who want a clear introduction to the methods …
This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity …
This collection of papers by leading researchers in their respective fields contains contributions showing the use of the maximum entropy …
This book is based on over a dozen years teaching a Bayesian Statistics course. The material presented here has been …
This volume has its origin in the third ·Workshop on Maximum-Entropy and Bayesian Methods in Applied Statistics,· held at the …
Bayesian statistical analyses have become increasingly common over the last two decades. The rapid increase in computing power that facilitated …
Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become …
The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets …
