Learn how to analyze data using Python models with the help of real-world use cases and guidance from industry expertsKey …
Increasingly, scientists and engineers must quickly and efficiently analyze and visualize extremely large sets of data. Interactive Data Language, IDL, …
This book proposes a data-driven methodology using multi-way data analysis for the design of video-quality metrics. It also enables video- …
Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0About This BookLearn why …
Книга является истоником быстрого ознакомления с SQL Server 2008. Скриншоты с содержанием прилагаются. . . . . . . . …
* Shows ordinary users how to tap the rich data analysis functionality of Excel, make sense of their organization's critical …
Perform time series analysis and forecasting confidently with this Python code bank and reference manualKey FeaturesExplore forecasting and anomaly detection …
This book constitutes the thoroughly refereed post-workshop proceedings of the 9th International Workshop on Mining Web Data, WEBKDD 2007, and …
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 …
The analysis of experimental data is at heart of science from its beginnings. But it was the advent of digital …
Ten years ago Bill Gale of AT&T Bell Laboratories was primary organizer of the first Workshop on Artificial Intelligence and …
Principles of Econometrics, Fifth Edition, is an introductory book for undergraduate students in economics and finance, as well as first-year …
This textbook provides an easy-to-understand introduction to the mathematical concepts and algorithms at the foundation of Data Science. It covers …
Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become …
This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, …
Machine Learning and Models for Optimization in Cloud’s main aim is to meet the user requirement with high quality of …
In social sciences, education, and public health research, researchers often conduct small pilot studies (or may have planned for a …
The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, …
This book provides a perspective on the application of machine learning-based methods in knowledge discovery from natural languages texts. By …
Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental …
This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together …
PRACTICAL TIME SERIES FORECASTING WITH R: A HANDS-ON GUIDE, SECOND EDITION provides an applied approach to time-series forecasting. Forecasting is …
There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis …
This book presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical …
This book presents the proceedings of The EAI International Conference on Computer Science: Applications in Engineering and Health Services (COMPSE …
Neil J. Salkind’s bestselling Statistics for People Who (Think They) Hate Statistics has been helping ease student anxiety around an …
