Learn IT - Books tags regression

Data Algorithms: Recipes for Scaling Up with Hadoop and Spark

O'Reilly, 2015

If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as...

Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition

Packt Publishing, 2018

An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms

Key Features

Explore statistics and complex mathematics for data-intensive applications

Discover new developments in EM algorithm, PCA, and bayesian...

Fixed Effects Regression Methods for Longitudinal Data Using SAS

SAS Institute, 2005

Every empirical researcher knows that randomized experiments have major advantages over observational studies in making causal inferences. Randomization of subjects to different treatment conditions ensures that the treatment groups, on average, are identical with respect to all possible characteristics of the subjects, regardless of whether those...

Introduction to the Mathematical and Statistical Foundations of Econometrics (Themes in Modern Econometrics)

Cambridge University Press, 2004

This book is intended for use in a rigorous introductory PhD level course in econometrics, or in a field course in econometric theory. It covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, central limit...

Access Data Analysis Cookbook

O'Reilly, 2007

If you have large quantities of data in a Microsoft Access database, and need to study that data in depth, this book is a data cruncher's dream. Access Data Analysis Cookbook offers practical recipes to solve a variety of common problems that users have with extracting Access data and performing calculations on it. Each recipe includes a...

Time Series Analysis and Its Applications: With R Examples (Springer Texts in Statistics)

Springer, 2010

Time Series Analysis and Its Applications presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception...

Hands-On Ensemble Learning with R: A beginner's guide to combining the power of machine learning algorithms using ensemble techniques

Packt Publishing, 2018

Explore powerful R packages to create predictive models using ensemble methods

Key Features

Implement machine learning algorithms to build ensemble-efficient models

Explore powerful R packages to create predictive models using ensemble methods

Learn to...

Hack Proofing Your Web Applications

Syngress Publishing, 2001

As a developer, the best possible way to focus on security is to begin to think like a hacker. Examine the methods that hackers use to break into and attack Web sites and use that knowledge to prevent attacks. You already test your code for functionality; one step further is to test it for security—attempt to break into it by finding some...

VMware ThinApp 4.7 Essentials

Packt Publishing, 2012

VMware ThinApp 4.7 is an application virtualization and portable application creator which allows users to package conventional applications so that they are portable.

"VMware ThinApp 4.7 Essentials" shows you how to deploy ThinApp packages in order to improve the portability, manageability and compatibility of...

Perl Medic : Transforming Legacy Code

Addison Wesley, 2004

Bring new power, performance, and scalability to your existing Perl code!

Today's Perl developers spend 60-80% of their time working with existing Perl code. Now, there's a start-to-finish guide to understanding that code, maintaining it, updating it, and refactoring it for maximum performance and reliability. Peter J. Scott, lead author of...

Getting Started With SAS Enterprise Miner 5.2

SAS Institute, 2006

SAS defines data mining as the process of uncovering hidden patterns in large amounts of data. Many industries use data mining to address business problems and opportunities such as fraud detection, risk and affinity analyses, database marketing, householding, customer churn, bankruptcy prediction, and...

Mashup Patterns: Designs and Examples for the Modern Enterprise

Addison Wesley, 2009

Using new mashup tools and technologies, enterprise developers can impose their own APIs on everything from Web sites and RSS feeds to Excel and PDF files–transforming a world of content into their own customized informationsource. In Mashup Patterns, Michael Ogrinz applies the concept of software development...

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