Master machine learning techniques with R to deliver complex and robust projects
If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful.
Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R-a cross-platform, zero-cost statistical programming environment-there has never been a better time to start applying machine learning to your data.
The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of "Unsupervised techniques." Finally, the book will walk you through text analysis and time series.
The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems.By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Cory Lesmeister has over fourteen years of quantitative experience and is currently a senior data scientist for the advanced analytics team at Cummins, Inc. in Columbus, Indiana. He has spent 16 years at Eli Lilly and Company in sales, market research, Lean Six Sigma, marketing analytics, and new product forecasting. He also has several years of experience in the insurance and banking industries, both as a consultant and as a manager of marketing analytics. A former US Army active duty and reserve officer, Cory was stationed in Baghdad, Iraq, in 2009. Here, he served as the strategic advisor to the 29,000-person Iraqi Oil Police, succeeding where others failed by acquiring and delivering promised equipment to help the country secure and protect its oil infrastructure. He has a BBA in aviation administration from the University of North Dakota and a commercial helicopter license.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : New. Master machine learning techniques with R to deliver insights for complex projectsAbout This Book. Get to grips with the application of Machine Learning methods using an extensive set of R packages. Understand the benefits and potential pitfalls of using machine learning methods. Implement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML systemWho This Book Is ForIf you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful.What You Will Learn. Gain deep insights to learn the applications of machine learning tools to the industry. Manipulate data in R efficiently to prepare it for analysis. Master the skill of recognizing techniques for effective visualization of data. Understand why and how to create test and training data sets for analysis. Familiarize yourself with fundamental learning methods such as linear and logistic regression. Comprehend advanced learning methods such as support vector machines. Realize why and how to apply unsupervised learning methodsIn DetailMachine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R-a cross-platform, zero-cost statistical programming environment-there has never been a better time to start applying machine learning to your data.The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of "Unsupervised techniques". Finally, the book will walk you through text analysis and time series.The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems. By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages.Style and approachThis is a book explains complicated concepts with easy to follow theory and real-world, practical applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints. N° de réf. du vendeur LU-9781783984527
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