Learn IT - Books tags regression

Scala Machine Learning Projects: Build real-world machine learning and deep learning projects with Scala

Packt Publishing, 2018

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming.

Key Features

Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j

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OpenCL Programming by Example

Packt Publishing, 2013

For a comprehensive, easy-to-swallow guide to OpenCL Programming, this book is out on its own. That's because it teaches through examples and covers everything from parallel sorting to optimization in simple stages.

Overview

Learn about all of the OpenCL Architecture and major APIs.

Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud

Apress, 2018

Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book?Amazon, Microsoft, Google, and PythonAnywhere.

You will work through a series of common Python data science problems...

Using R for Statistics

Apress, 2014

Using R for Statistics will get you the answers to most of the problems you are likely to encounter when using a variety of statistics. This book is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks you through R basics and how to use...

How Financial Slack Affects Corporate Performance: An Examination in an Uncertain and Resource Scarce Environment (BestMasters)

Springer, 2013

Bernadette Gral examines the relationship between financial slack and corporate performance in the European pharmaceutical industry during the financial crisis of 2007 to 2010. Her investigation includes correlational and regression analyses as well as the qualitative content analysis of newspaper articles. The results show that financial...

SAS/STAT 9.22 User's Guide:: The PHREG Procedure (Book Excerpt)

SAS Institute, 2010

The PHREG procedure performs regression analysis of survival data based on the Cox proportional hazards model and its extensions.

The analysis of survival data requires special techniques because the data are almost always incomplete and familiar parametric assumptions might be unjustifiable. Investigators follow subjects until...

Scala for Machine Learning

Packt Publishing, 2014

Leverage Scala and Machine Learning to construct and study systems that can learn from data

About This Book

Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and source code

Leverage your expertise in Scala...

Introduction to Data Analysis and Graphical Presentation in Biostatistics with R: Statistics in the Large (SpringerBriefs in Statistics)

Springer, 2013

Through real-world datasets, this book shows the reader how to work with material in biostatistics using the open source software R. These include tools that are critical to dealing with missing data, which is a pressing scientific issue for those engaged in biostatistics. Readers will be equipped to run analyses and make graphical...

The Analyst Application

SAS Institute, 2003

This guide will show you how to use the Analyst Application to perform such tasks as table analysis, ANOVA, repeated measurements, mixed models, basic power computations, and much more.

Discover how to perform statistical analysis using the Analyst Application, a point-and-click interface to basic statistical analysis in SAS. The...

Analyzing Rater Agreement: Manifest Variable Methods

Lawrence Erlbaum Associates, 2004

Agreement among raters is of great importance in many domains. For example, in medicine, diagnoses are often provided by more than one doctor to make sure the proposed treatment is optimal. In criminal trials, sentencing depends, among other things, on the complete agreement among the jurors. In observational studies, researchers increase...

Computer Vision: Models, Learning, and Inference

Cambridge University Press, 2012

There are already many computer vision textbooks, and it is reasonable to question the need for another. Let me explain why I chose to write this volume.

Computer vision is an engineering discipline; we are primarily motivated by the real-world concern of...

Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks

Apress, 2018

Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and...

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