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Hands-On Machine Learning with R (Chapman & Hall/CRC The R Series) de Brad Boehmke,Brandon M. Greenwell

Descripción - Críticas 'Hands-On Machine Learning with R is a great resource for understanding and applying models. Each section provides descriptions and instructions using a wide range of R packages.' - Max Kuhn, Machine Learning Software Engineer, RStudio 'You can't find a better overview of practical machine learning methods implemented with R.'- JD Long, co-author of R Cookbook 'Simultaneously approachable, accessible, and rigorous, Hands-On Machine Learning with R offers a balance of theory and implementation that can actually bring you from relative novice to competent practitioner.' - Mara Averick, RStudio Dev Advocate Reseña del editor Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory.  Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: ·         Offers a practical and applied introduction to the most popular machine learning methods. ·         Topics covered include feature engineering, resampling, deep learning and more. ·         Uses a hands-on approach and real world data. Biografía del autor Brad Boehmke is a data scientist at 84.51° where he wears both software developer and machine learning engineer hats. He is an Adjunct Professor at the University of Cincinnati, author of Data Wrangling with R, and creator of multiple public and private enterprise R packages.

Brandon Greenwell is a data scientist at 84.51° where he works on a diverse team to enable, empower, and encourage others to successfully apply machine learning to solve real business problems. He’s part of the Adjunct Graduate Faculty at Wright State University, an Adjunct Instructor at the University of Cincinnati, and the author of several R packages available on CRAN.

Machine learning mastery with r machine learning mastery with r is a great book for anyone looking to get started with machine learning the book gives details how each step of a machine learning project should go from descriptive statistics, to model selection and tuning, to predictions Handson machine learning with r bradley boehmke the book favors a handson approach, growing an intuitive understanding of machine learning through concrete examples and just a little bit of theory while you can read this book without opening r, we highly recommend you experiment with the code examples provided throughout Machine learning course machine learning certification machine learning is in high demand but before you jump into certification training, its essential for beginners to get familiar with the basics of machine learning first simplilearns free resources articles, tutorials, and youtube videos will help you get a handle on the concepts and techniques of machine learning

Github rasbtpythonmachinelearningbook2ndedition the python machine learning 2nd edition book code repository and info resource rasbtpythonmachinelearningbook2ndedition Introduction to machine learning online course datacamp this online machine learning course is perfect for those who have a solid basis in r and statistics, but are complete beginners with machine learning after a broad overview of the disciplines most common techniques and applications, youll gain more insight into the assessment and training of different machine learning models Introduction machine learning artificial intelligence machine learning methods can be used for onthejob improvement of existing machine designs the amount of knowledge available about certain tasks might be too large for explicit encoding by humans machines that learn this knowledge gradually might be able to capture more of it than humans would want to

Detalles del Libro

• Name: Hands-On Machine Learning with R (Chapman & Hall/CRC The R Series)
  
• Autor: Brad Boehmke,Brandon M. Greenwell
  
• Categoria: Libros,Ciencias, tecnología y medicina,Matemáticas
  
• Tamaño del archivo: 17 MB
  
• Tipos de archivo: PDF Document
  
• Idioma: Español
  
• Archivos de estado: AVAILABLE
  

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