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Mastering Machine Learning With R

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Mastering Machine Learning With R

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Author : Cory Lesmeister
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-10-28

Mastering Machine Learning With R written by Cory Lesmeister and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-28 with Computers categories.

Master machine learning techniques with R to deliver insights for complex projects About 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 system Who This Book Is For 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. 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 methods In Detail 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. Style and approach This 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.

Mastering Machine Learning With R

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Author : Cory Lesmeister
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-01-31

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 FeaturesBuild independent machine learning (ML) systems leveraging the best features of R 3.5Understand and apply different machine learning techniques using real-world examplesUse methods such as multi-class classification, regression, and clusteringBook 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 learnPrepare data for machine learning methods with easeUnderstand how to write production-ready code and package it for useProduce simple and effective data visualizations for improved insightsMaster advanced methods, such as Boosted Trees and deep neural networksUse natural language processing to extract insights in relation to textImplement tree-based classifiers, including Random Forest and Boosted TreeWho 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 advanced machine learning algorithms. The book will help you take your skills to the next level and advance further in this field. Working knowledge of machine learning with R is mandatory.

Mastering Machine Learning With R Third Edition

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Author : Cory Lesmeister
language : en
Publisher:
Release Date : 2019

Mastering Machine Learning With R Third Edition written by Cory Lesmeister and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

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 Mastery With R

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Author : Jason Brownlee
language : en
Publisher: Machine Learning Mastery
Release Date : 2016-01-30

Machine Learning Mastery With R written by Jason Brownlee and has been published by Machine Learning Mastery this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-30 with Computers categories.

R has been the gold standard in applied machine learning for a long time. Surveys show that it is the most popular platform used by professional data scientists. It is also preferred by the best data scientists in the world. In this Ebook, learn how to get started, practice and apply machine learning using the R platform.

Mastering Predictive Analytics With R

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Author : Rui Miguel Forte
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-06-17

Mastering Predictive Analytics With R written by Rui Miguel Forte and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-17 with Computers categories.

R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems. This book is designed to be both a guide and a reference for moving beyond the basics of predictive modeling. The book begins with a dedicated chapter on the language of models and the predictive modeling process. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real world data sets. By the end of this book, you will have explored and tested the most popular modeling techniques in use on real world data sets and mastered a diverse range of techniques in predictive analytics.

Machine Learning In R For Everyone

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Author : Jonathan Wayne Korn, PhD
language : en
Publisher: Independently Published
Release Date : 2023-09-09

Machine Learning In R For Everyone written by Jonathan Wayne Korn, PhD and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-09 with categories.

"Machine Learning in R for Everyone" is your comprehensive guide to mastering machine learning with the R programming language. Whether you're a novice looking to embark on your data science journey or an experienced practitioner aiming to refine your skills, this book provides a structured and hands-on approach to understanding and implementing machine learning concepts. Starting with the fundamentals, the book introduces you to machine learning algorithms, data manipulation, and analysis tools in R. Through practical examples, you'll learn to collect, preprocess, and explore data, gaining insights into data-driven decision-making. The book covers regression, classification, and time series forecasting, equipping you with the knowledge to build predictive models effectively. You'll delve into model evaluation techniques, feature engineering, and model interpretation, ensuring you can not only create models but also optimize their performance. By the end of the book, you'll be proficient in various machine learning algorithms and visualization techniques, ready to tackle real-world challenges with confidence. "Machine Learning in R for Everyone" is your gateway to unleashing the power of machine learning for practical applications in R.

R

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Author : Raghav Bali
language : en
Publisher:
Release Date : 2017-06-19

R written by Raghav Bali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-19 with Computers categories.

Find out how to build smarter machine learning systems with R. Follow this three module course to become a more fluent machine learning practitioner.About This Book* Build your confidence with R and find out how to solve a huge range of data-related problems* Get to grips with some of the most important machine learning techniques being used by data scientists and analysts across industries today* Don't just learn - apply your knowledge by following featured practical projects covering everything from financial modeling to social media analysisWho This Book Is ForAimed for intermediate-to-advanced people (especially data scientist) who are already into the field of data scienceWhat You Will Learn* Get to grips with R techniques to clean and prepare your data for analysis, and visualize your results* Implement R machine learning algorithms from scratch and be amazed to see the algorithms in action* Solve interesting real-world problems using machine learning and R as the journey unfolds* Write reusable code and build complete machine learning systems from the ground up* Learn specialized machine learning techniques for text mining, social network data, big data, and more* Discover the different types of machine learning models and learn which is best to meet your data needs and solve your analysis problems* Evaluate and improve the performance of machine learning models* Learn specialized machine learning techniques for text mining, social network data, big data, and moreIn DetailR is the established language of data analysts and statisticians around the world. And you shouldn't be afraid to use it...This Learning Path will take you through the fundamentals of R and demonstrate how to use the language to solve a diverse range of challenges through machine learning. Accessible yet comprehensive, it provides you with everything you need to become more a more fluent data professional, and more confident with R. In the first module you'll get to grips with the fundamentals of R. This means you'll be taking a look at some of the details of how the language works, before seeing how to put your knowledge into practice to build some simple machine learning projects that could prove useful for a range of real world problems.For the following two modules we'll begin to investigate machine learning algorithms in more detail. To build upon the basics, you'll get to work on three different projects that will test your skills. Covering some of the most important algorithms and featuring some of the most popular R packages, they're all focused on solving real problems in different areas, ranging from finance to social media.This Learning Path has been curated from three Packt products:* R Machine Learning By Example By Raghav Bali, Dipanjan Sarkar* Machine Learning with R Learning - Second Edition By Brett Lantz* Mastering Machine Learning with R By Cory LesmeisterStyle and approachThis is an enticing learning path that starts from the very basics to gradually pick up pace as the story unfolds. Each concept is first defined in the larger context of things succinctly, followed by a detailed explanation of their application. Each topic is explained with the help of a project that solves a real-world problem involving hands-on work thus giving you a deep insight into the world of machine learning.

Advanced Machine Learning With R

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Author : Cory Lesmeister
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-20

Advanced Machine Learning With R written by Cory Lesmeister and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-20 with Computers categories.

Master machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages Key FeaturesGain expertise in machine learning, deep learning and other techniquesBuild intelligent end-to-end projects for finance, social media, and a variety of domainsImplement multi-class classification, regression, and clusteringBook Description R is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You'll tackle realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. You'll explore different clustering techniques to segment customers using wholesale data and use TensorFlow and Keras-R for performing advanced computations. You’ll also be introduced to reinforcement learning along with its various use cases and models. Additionally, it shows you how some of these black-box models can be diagnosed and understood. By the end of this Learning Path, you’ll be equipped with the skills you need to deploy machine learning techniques in your own projects. This Learning Path includes content from the following Packt products: R Machine Learning Projects by Dr. Sunil Kumar ChinnamgariMastering Machine Learning with R - Third Edition by Cory LesmeisterWhat you will learnDevelop a joke recommendation engine to recommend jokes that match users’ tastesBuild autoencoders for credit card fraud detectionWork with image recognition and convolutional neural networksMake predictions for casino slot machine using reinforcement learningImplement NLP techniques for sentiment analysis and customer segmentationProduce simple and effective data visualizations for improved insightsUse NLP to extract insights for textImplement tree-based classifiers including random forest and boosted treeWho this book is for If you are a data analyst, data scientist, or machine learning developer this is an ideal Learning Path for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this Learning Path.

Mastering Predictive Analytics With R

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Author : James D. Miller
language : en
Publisher:
Release Date : 2017

Mastering Predictive Analytics With R written by James D. Miller and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with R (Computer program language) categories.

Master the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential concepts About This Book Grasping the major methods of predictive modeling and moving beyond black box thinking to a deeper level of understanding Leveraging the flexibility and modularity of R to experiment with a range of different techniques and data types Packed with practical advice and tips explaining important concepts and best practices to help you understand quickly and easily Who This Book Is For Although budding data scientists, predictive modelers, or quantitative analysts with only basic exposure to R and statistics will find this book to be useful, the experienced data scientist professional wishing to attain master level status , will also find this book extremely valuable.. This book assumes familiarity with the fundamentals of R, such as the main data types, simple functions, and how to move data around. Although no prior experience with machine learning or predictive modeling is required, there are some advanced topics provided that will require more than novice exposure. What You Will Learn Master the steps involved in the predictive modeling process Grow your expertise in using R and its diverse range of packages Learn how to classify predictive models and distinguish which models are suitable for a particular problem Understand steps for tidying data and improving the performing metrics Recognize the assumptions, strengths, and weaknesses of a predictive model Understand how and why each predictive model works in R Select appropriate metrics to assess the performance of different types of predictive model Explore word embedding and recurrent neural networks in R Train models in R that can work on very large datasets In Detail R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems. The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real-world datasets. How do y...

Mastering Predictive Analytics With R

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Author : James D. Miller
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-08-18

Mastering Predictive Analytics With R written by James D. Miller and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-18 with Computers categories.

Mastering Machine Learning With R

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