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Interpreting and Visualizing Regression Models Using Stata
Interpreting and Visualizing Regression Models Using Stata

Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using polynomials,...

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

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...

Learning Predictive Analytics with Python: Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python
Learning Predictive Analytics with Python: Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

About This Book

  • A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices
  • Get to grips with the basics of Predictive...
Data Analysis Using Regression and Multilevel/Hierarchical Models
Data Analysis Using Regression and Multilevel/Hierarchical Models

Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using...

Data Analysis Using SAS Enterprise Guide
Data Analysis Using SAS Enterprise Guide

The present book, Data Analysis Using SAS Enterprise Guide, provides readers with an overview of Enterprise Guide, the newest point-and-click interface from SAS. SAS Enterprise Guide is a graphical user (point-and-click) interface to the main SAS application, having relatively recently replaced the Analyst interface, which itself had replaced...

Introductory Statistics with R (Statistics and Computing)
Introductory Statistics with R (Statistics and Computing)
This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the...
Machine Learning in Action
Machine Learning in Action

After college I went to work for Intel in California and mainland China. Originally my plan was to go back to grad school after two years, but time flies when you are having fun, and two years turned into six. I realized I had to go back at that point, and I didn’t want to do night school or online learning, I wanted to sit on...

Practical Business Analytics Using SAS: A Hands-on Guide
Practical Business Analytics Using SAS: A Hands-on Guide

Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios.

The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data...

Multi-objective Management in Freight Logistics: Increasing Capacity, Service Level and Safety with Optimization Algorithms
Multi-objective Management in Freight Logistics: Increasing Capacity, Service Level and Safety with Optimization Algorithms
The complexity of modern supply chains requires decision makers in logistics to work with a set of efficient (Pareto optimal) solutions, mainly to catch different economic aspects for which one optimal solution related to a single objective function is not able to capture entirely. Motivated by this, and by recent changes in global markets and the...
Advanced Data Mining Techniques
Advanced Data Mining Techniques
This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a...
Getting Started With SAS Enterprise Miner 5.2
Getting Started With SAS Enterprise Miner 5.2
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...
Assessing and Improving Prediction and Classification: Theory and Algorithms in C++
Assessing and Improving Prediction and Classification: Theory and Algorithms in C++
Assess the quality of your prediction and classification models in ways that accurately reflect their real-world performance, and then improve this performance using state-of-the-art algorithms such as committee-based decision making, resampling the dataset, and boosting.  This book presents many important techniques for building...
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