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9781491976449 - Introduction to Machine Learning with R: Rigorous Mathematical Analysis di Burger, Scott V (25 risultati)
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Introduction to Machine Learning with R: Rigorous Mathematical Analysis
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Introduction to Machine Learning with R
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Introduction to Machine Learning With R : Rigorous Mathematical Analysis
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Introduction to Machine Learning With R : Rigorous Mathematical Analysis
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Introduction to Machine Learning with R
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Aggiungi al carrelloPaperback. Condizione: New. Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you'll first start to learn with regression modelling and then move into more advanced topics such as neural networks and tree-based methods. Finally, you'll delve into the frontier of machine learning, using the caret package in R. Once you develop a familiarity with topics such as the difference between regression and classification models, you'll be able to solve an array of machine learning problems. Author Scott V. Burger provides several examples to help you build a working knowledge of machine learning. Explore machine learning models, algorithms, and data training Understand machine learning algorithms for supervised and unsupervised cases Examine statistical concepts for designing data for use in models Dive into linear regression models used in business and science Use single-layer and multilayer neural networks for calculating outcomes Look at how tree-based models work, including popular decision trees Get a comprehensive view of the machine learning ecosystem in R Explore the powerhouse of tools available in R's caret package.
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Introduction to Machine Learning with R: Rigorous Mathematical Analysis (Paperback or Softback)
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Aggiungi al carrelloPaperback. Condizione: New. Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you'll first start to learn with regression modelling and then move into more advanced topics such as neural networks and tree-based methods. Finally, you'll delve into the frontier of machine learning, using the caret package in R. Once you develop a familiarity with topics such as the difference between regression and classification models, you'll be able to solve an array of machine learning problems. Author Scott V. Burger provides several examples to help you build a working knowledge of machine learning. Explore machine learning models, algorithms, and data training Understand machine learning algorithms for supervised and unsupervised cases Examine statistical concepts for designing data for use in models Dive into linear regression models used in business and science Use single-layer and multilayer neural networks for calculating outcomes Look at how tree-based models work, including popular decision trees Get a comprehensive view of the machine learning ecosystem in R Explore the powerhouse of tools available in R's caret package.
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INTRODUCTION TO MACHINE LEARNING WITH R
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Introduction to Machine Learning With R : Rigorous Mathematical Analysis
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Introduction to Machine Learning with R: Rigorous Mathematical Analysis
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Introduction to Machine Learning with R: Rigorous Mathematical Analysis
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Introduction to Machine Learning With R : Rigorous Mathematical Analysis
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Introduction to Machine Learning With R: Rigorous Mathematical Analysis
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Aggiungi al carrelloPaperback. Condizione: Brand New. 212 pages. 9.00x7.00x0.50 inches. In Stock.
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Introduction to Machine Learning with R
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Introduction to Machine Learning with R
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Introduction to Machine Learning with R
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Introduction to Machine Learning With R: Rigorous Mathematical Analysis
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Aggiungi al carrelloPaperback. Condizione: Brand New. 212 pages. 9.00x7.00x0.50 inches. In Stock.
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INTRODUCTION TO MACHINE LEARNING WITH R
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Introduction to Machine Learning with R
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Aggiungi al carrelloPaperback. Condizione: New. Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you'll first start to learn with regression modelling and then move into more advanced topics such as neural networks and tree-based methods. Finally, you'll delve into the frontier of machine learning, using the caret package in R. Once you develop a familiarity with topics such as the difference between regression and classification models, you'll be able to solve an array of machine learning problems. Author Scott V. Burger provides several examples to help you build a working knowledge of machine learning. Explore machine learning models, algorithms, and data training Understand machine learning algorithms for supervised and unsupervised cases Examine statistical concepts for designing data for use in models Dive into linear regression models used in business and science Use single-layer and multilayer neural networks for calculating outcomes Look at how tree-based models work, including popular decision trees Get a comprehensive view of the machine learning ecosystem in R Explore the powerhouse of tools available in R's caret package.
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Aggiungi al carrelloCondizione: New. Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles.Über den AutorSco.
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Introduction to Machine Learning with R
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Aggiungi al carrelloPaperback. Condizione: New. Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you'll first start to learn with regression modelling and then move into more advanced topics such as neural networks and tree-based methods. Finally, you'll delve into the frontier of machine learning, using the caret package in R. Once you develop a familiarity with topics such as the difference between regression and classification models, you'll be able to solve an array of machine learning problems. Author Scott V. Burger provides several examples to help you build a working knowledge of machine learning. Explore machine learning models, algorithms, and data training Understand machine learning algorithms for supervised and unsupervised cases Examine statistical concepts for designing data for use in models Dive into linear regression models used in business and science Use single-layer and multilayer neural networks for calculating outcomes Look at how tree-based models work, including popular decision trees Get a comprehensive view of the machine learning ecosystem in R Explore the powerhouse of tools available in R's caret package.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware - Machine learning can be a difficult subject if you're not familiar with the basics. With this book, you'll get a solid foundation of introductory principles used in machine learning with the statistical programming language R. You'll start with the basics like regression, then move into more advanced topics like neural networks, and finally delve into the frontier of machine learning in the R world with packages like Caret. By developing a familiarity with topics like understanding the difference between regression and classification models, you'll be able to solve an array of machine learning problems. Knowing when to use a specific model or not can mean the difference between a highly accurate model and a completely useless one. This book provides copious examples to build a working knowledge of machine learning. Understand the major parts of machine learning algorithms Recognize how machine learning can be used to solve a problem in a simple manner Figure out when to use certain machine learning algorithms versus others Learn how to operationalize algorithms with cutting edge packages.
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EUR 56,35
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Introduction to Machine Learning with R | Rigorous Mathematical Analysis | Burger Scott | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2018 | O'Reilly Media | EAN 9781491976449 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
