Mastering machine learning with R: advanced machine learning techniques for building smart applications with R 3.5
Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key Features Build independent machine learning (ML) systems leveraging the best features of R 3.5 Understand and apply different mach...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Birmingham, UK
Packt Publishing
2019
|
| Ausgabe: | Third edition. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781789618006/?ar |
| Zusammenfassung: | Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key Features Build independent machine learning (ML) systems leveraging the best features of R 3.5 Understand and apply different machine learning techniques using real-world examples Use methods such as multi-class classification, regression, and clustering Book Description Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML, using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You'll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you'll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You'll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you'll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you'll be equipped with the skills to deploy ML techniques in your own projects or at work. What you will learn Prepare data for machine learning methods with ease Understand how to write production-ready code and package it for use Produce simple and effective data visualizations for improved insights Master advanced methods, such as Boosted Trees and deep neural networks Use natural language processing to extract insights in relation to text Implement tree-based classifiers, including Random Forest and Boosted Tree Who this book is for This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement ... |
| Beschreibung: | Previous edition published: 2017. - Includes bibliographical references. - Online resource; title from title page (Safari, viewed March 25, 2019) |
| Umfang: | 1 Online-Ressource (1 volume) illustrations |
| ISBN: | 9781789613568 1789613566 9781789618006 |
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| spelling | Lesmeister, Cory VerfasserIn aut Mastering machine learning with R advanced machine learning techniques for building smart applications with R 3.5 Cory Lesmeister Third edition. Birmingham, UK Packt Publishing 2019 1 Online-Ressource (1 volume) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Previous edition published: 2017. - Includes bibliographical references. - Online resource; title from title page (Safari, viewed March 25, 2019) Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key Features Build independent machine learning (ML) systems leveraging the best features of R 3.5 Understand and apply different machine learning techniques using real-world examples Use methods such as multi-class classification, regression, and clustering Book Description Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML, using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You'll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you'll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You'll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you'll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you'll be equipped with the skills to deploy ML techniques in your own projects or at work. What you will learn Prepare data for machine learning methods with ease Understand how to write production-ready code and package it for use Produce simple and effective data visualizations for improved insights Master advanced methods, such as Boosted Trees and deep neural networks Use natural language processing to extract insights in relation to text Implement tree-based classifiers, including Random Forest and Boosted Tree Who this book is for This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement ... Machine learning R (Computer program language) Apprentissage automatique R (Langage de programmation) MATHEMATICS ; Applied MATHEMATICS ; Probability & Statistics ; General 1789618002 Erscheint auch als Druck-Ausgabe 1789618002 |
| spellingShingle | Lesmeister, Cory Mastering machine learning with R advanced machine learning techniques for building smart applications with R 3.5 Machine learning R (Computer program language) Apprentissage automatique R (Langage de programmation) MATHEMATICS ; Applied MATHEMATICS ; Probability & Statistics ; General |
| title | Mastering machine learning with R advanced machine learning techniques for building smart applications with R 3.5 |
| title_auth | Mastering machine learning with R advanced machine learning techniques for building smart applications with R 3.5 |
| title_exact_search | Mastering machine learning with R advanced machine learning techniques for building smart applications with R 3.5 |
| title_full | Mastering machine learning with R advanced machine learning techniques for building smart applications with R 3.5 Cory Lesmeister |
| title_fullStr | Mastering machine learning with R advanced machine learning techniques for building smart applications with R 3.5 Cory Lesmeister |
| title_full_unstemmed | Mastering machine learning with R advanced machine learning techniques for building smart applications with R 3.5 Cory Lesmeister |
| title_short | Mastering machine learning with R |
| title_sort | mastering machine learning with r advanced machine learning techniques for building smart applications with r 3 5 |
| title_sub | advanced machine learning techniques for building smart applications with R 3.5 |
| topic | Machine learning R (Computer program language) Apprentissage automatique R (Langage de programmation) MATHEMATICS ; Applied MATHEMATICS ; Probability & Statistics ; General |
| topic_facet | Machine learning R (Computer program language) Apprentissage automatique R (Langage de programmation) MATHEMATICS ; Applied MATHEMATICS ; Probability & Statistics ; General |
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