Mastering Machine Learning with R - Second Edition by Cory Lesmeister

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Author: Cory Lesmeister
Category: Engineering & IT
ISBN: 9781787284487
File Size: 4.96 MB
Format: EPUB (e-book)
DRM: Applied (Requires eSentral Reader App)
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Key FeaturesUnderstand and apply machine learning methods using an extensive set of R packages such as XGBOOSTUnderstand the benefits and potential pitfalls of using machine learning methods such as Multi-Class Classification and Unsupervised LearningImplement advanced concepts in machine learning with this example-rich guideBook DescriptionThis book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating Recommendation Engines; use multi-class classification and deep learning; and more.You will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. More than just knowing the outcome, youll understand how these concepts work and what they do.With a slow learning curve on topics such as neural networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets.What you will learnGain deep insights into the application of machine learning tools in the industryManipulate data in R efficiently to prepare it for analysisMaster the skill of recognizing techniques for effective visualization of dataUnderstand why and how to create test and training data sets for analysisMaster fundamental learning methods such as linear and logistic regressionComprehend advanced learning methods such as support vector machinesLearn how to use R in a cloud service such as AmazonAbout the AuthorCory Lesmeister has over a dozen years of quantitative experience and is currently a Senior Quantitative Manager in the banking industry, responsible for building marketing and regulatory models. Cory spent 16 years at Eli Lilly and Company in sales, market research, Lean Six Sigma, marketing analytics, and new product forecasting. A former U.S. Army active duty and reserve officer, Cory was in Baghdad, Iraq, in 2009 serving as the strategic advisor to the 29,000-person Iraqi Oil Police, where he supplied equipment to help the country secure and protect its oil infrastructure. An aviation aficionado, Cory has a BBA in aviation administration from the University of North Dakota and a commercial helicopter license.Table of ContentsA Process for SuccessLinear Regression - The Blocking and Tackling of Machine LearningLogistic Regression and Discriminant AnalysisAdvanced Feature Selection in Linear ModelsMore Classification Techniques - K-Nearest Neighbors and Support Vector MachinesClassification and Regression TreesNeural Networks and Deep LearningCluster AnalysisPrincipal Components AnalysisMarket Basket Analysis, Recommendation Engines, and Sequential AnalysisCreating Ensembles and Multiclass ClassificationTime Series and CausalityText MiningR on the CloudR FundamentalsSources


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