Machine Learning With R Cookbook - 110 Recipes for Building Powerful Predictive Models with R, by Yu-Wei, Chiu (David Chiu)
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Machine Learning With R Cookbook - 110 Recipes for Building Powerful Predictive Models with R, by Yu-Wei, Chiu (David Chiu)
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Key Features
- Apply R to simplify predictive modeling with short and simple code
- Use machine learning to solve problems ranging from small to big data
- Build a training and testing dataset from the churn dataset, applying different classification methods
Book Description
The R language is a powerful open source functional programming language. At its core, R is a statistical programming language that provides impressive tools to analyze data and create high-level graphics.
This book covers the basics of R by setting up a user-friendly programming environment and performing data ETL in R. Data exploration examples are provided that demonstrate how powerful data visualization and machine learning is in discovering hidden relationships. You will then dive into important machine learning topics, including data classification, regression, clustering, association rule mining, and dimension reduction.
What you will learn
- Create and inspect the transaction dataset, performing association analysis with the Apriori algorithm
- Visualize patterns and associations using a range of graphs and find frequent itemsets using the Eclat algorithm
- Compare differences between each regression method to discover how they solve problems
- Predict possible churn users with the classification approach
- Implement the clustering method to segment customer data
- Compress images with the dimension reduction method
- Incorporate R and Hadoop to solve machine learning problems on Big Data
About the Author
Yu-Wei, Chiu (David Chiu) is the founder of Largit Data. He has previously worked for Trend Micro as a software engineer, with the responsibility of building big data platforms for business intelligence and customer relationship management systems. In addition to being a start-up entrepreneur and data scientist, he specializes in using Spark and Hadoop to process big data and apply data mining techniques for data analysis.
Table of Contents
Practical Machine Learning with RData Exploration with RMS TitanicR and StatisticsUnderstanding Regression AnalysisClassification (I) Tree, Lazy, and ProbabilisticClassification (II) Neural Network and SVMModel EvaluationEnsemble LearningClusteringAssociation Analysis and Sequence MininDimension ReductionBig Data Analysis (R and Hadoop) Machine Learning With R Cookbook - 110 Recipes for Building Powerful Predictive Models with R, by Yu-Wei, Chiu (David Chiu) - Amazon Sales Rank: #318136 in Books
- Published on: 2015-03-31
- Released on: 2015-03-26
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 1.00" w x 7.50" l, 1.66 pounds
- Binding: Paperback
- 405 pages
Machine Learning With R Cookbook - 110 Recipes for Building Powerful Predictive Models with R, by Yu-Wei, Chiu (David Chiu) About the Author
Yu-Wei, Chiu (David Chiu)
Yu-Wei, Chiu (David Chiu) is the founder of LargitData. He has previously worked for Trend Micro as a software engineer, with the responsibility of building big data platforms for business intelligence and customer relationship management systems. In addition to being a start-up entrepreneur and data scientist, he specializes in using Spark and Hadoop to process big data and apply data mining techniques for data analysis. Yu-Wei is also a professional lecturer and has delivered lectures on Python, R, Hadoop, and tech talks at a variety of conferences. In 2013, Yu-Wei reviewed Bioinformatics with R Cookbook, Packt Publishing.
Where to Download Machine Learning With R Cookbook - 110 Recipes for Building Powerful Predictive Models with R, by Yu-Wei, Chiu (David Chiu)
Most helpful customer reviews
8 of 8 people found the following review helpful. A very good book that complements other machine learning sources By GES Since books are expensive, I tend to research extensively before deciding on which ones to purchase. For professional reasons, I wanted to branch into machine learning using the R programming language. Based on customer reviews, the Amazon “Look Inside” feature, and online suggestions, I invested in several books: “An Introduction to Statistical Learning with Applications in R” (James, Whitten, Hastie and Tibshirani), “Artificial Intelligence, A Modern Approach, Third Edition” (Russell and Norvig), “Machine Learning with R” (Lantz), and “Machine Learning with R Cookbook” (Chiu). With these resources, and with a great YouTube course from the University of British Columbia (Google UBC CPSC 340 Nando YouTube), I set out to learn. Still learning (no overnight success stories here), but the progress is encouraging.So, what? Building useful skills in machine learning from scratch, I believe, requires a tool chest of resources. As hard as I tried, I couldn’t find a single “do-all” book.The Machine Learning with R Cookbook will not teach you about machine learning and it will not broadly cover every aspect of R. There are better sources for that, both online and in print. What this book does, and does quite well, is provide you with real-world examples of applying R to machine learning. Lots of consistent structure (most examples contain “Getting ready”, “How to do it”, “How it works”, and “See also” sections), tons of code, and over 100 sample recipes using readily available and diverse data sets. If you learn by reading, watching, and doing, I believe this book is very worthwhile addition in your professional tool chest.
5 of 5 people found the following review helpful. First-best in the second-best category By Dimitri Shvorob Even a dog can publish a book with Packt: the publisher operates a no-editors, no-graphic-designers, no-standards business model and publishes anything by anybody, hoping that something sticks. In the hot "data science / machine learning" segment, Packt met 2015 with a bang, churning out the god-awful "Learning Data Mining with R" by Makhabel and "R for Data Science" by Toomey. Then four more titles came out:"Mastering Predictive Analytics with R" by Forte, $45"Mastering Machine Learning with R" by Lesmeister, $40"R Data Analysis Cookbook" by Viswanathan and Viswanathan, $40"Machine Learning with R Cookbook" by Yu-Wei, $40I checked them out and, long story short, "Mastering Predictive Analytics with R" - let me call it "MPAR" - is a winner, "Mastering Machine Learning with R" is a dog, while "R Data Analysis Cookbook" and "Machine Learning with R Cookbook" ("MLRC", then) fall somewhere in between. "R Data Analysis Cookbook" is clearly "dominated" by MLRC on machine-learning content - but MLRC itself seems to be bested by MPAR. MPAR covers much the same territory, but, unlike MLRC, can coherently explain the algorithms, whereas MLRC is helpless. MLRC is the best book in the low-value-added code-without-understanding category - the books by Makhabel, Toomey and Lesmeister are soul-destroying - but I would still suggest you go with MPAR. Better yet, prioritize learning over hacking, and start with "Introduction to statistical learning" by James et al.PS. If you see any odd things in "Comments", that's probably the psycho who has spent days posting offensive comments to my reviews - only for them to be deleted by Amazon - after I criticized an iffy Packt book promoted with questionable five-star reviews. ("R Machine Learning By Example" by Bali and Sarkar, if you are wondering). As long as you know that his "Dimitri Shvorob" is fake, there isn't much harm he can do.
1 of 1 people found the following review helpful. Great book for R newbies! By May Yang I highly recommend this book to everyone, especially for those R newbies! I was also a complete novice in R language and machine learning field, but with the help of this book, in just 1 month, I was able to well understand the general picture of R language application, and stepping right into machine learning concept by using R.The content of this book is designed in a very organized way, step by step it teaches us from basic concept to some sort of advanced stuff, thus I would sincerely suggest whoever buys it to read from the beginning, and practice those R codes shown on the book along the way when you are reading it. I got a lot of enlightens when I read it earlier, I hope you can get the same feeling as I did after purchasing. Cheers!
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Machine Learning With R Cookbook - 110 Recipes for Building Powerful Predictive Models with R, by Yu-Wei, Chiu (David Chiu)
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Machine Learning With R Cookbook - 110 Recipes for Building Powerful Predictive Models with R, by Yu-Wei, Chiu (David Chiu)
Machine Learning With R Cookbook - 110 Recipes for Building Powerful Predictive Models with R, by Yu-Wei, Chiu (David Chiu)
Machine Learning With R Cookbook - 110 Recipes for Building Powerful Predictive Models with R, by Yu-Wei, Chiu (David Chiu)
Machine Learning With R Cookbook - 110 Recipes for Building Powerful Predictive Models with R, by Yu-Wei, Chiu (David Chiu)
