Machine Learning with R - Fourth Edition: Learn techniques for building and i...
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Item specifics
- Condition
- Book Title
- Machine Learning with R - Fourth Edition: Learn techniques for bu
- ISBN
- 9781801071321
- Publication Year
- 2023
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Subject Area
- Computers, Science
- Publication Name
- Machine Learning with R : Learn Data Cleansing to Modeling from the Tidyverse to Neural Networks and Working with Big Data
- Publisher
- Packt Publishing, The Limited
- Item Length
- 92.5 in
- Subject
- Electronic Commerce (See Also Headings under Business & Economics / E-Commerce), General
- Item Width
- 75 in
- Number of Pages
- 606 Pages
About this product
Product Identifiers
Publisher
Packt Publishing, The Limited
ISBN-10
1801071322
ISBN-13
9781801071321
eBay Product ID (ePID)
18060728456
Product Key Features
Number of Pages
606 Pages
Language
English
Publication Name
Machine Learning with R : Learn Data Cleansing to Modeling from the Tidyverse to Neural Networks and Working with Big Data
Publication Year
2023
Subject
Electronic Commerce (See Also Headings under Business & Economics / E-Commerce), General
Type
Textbook
Subject Area
Computers, Science
Format
Trade Paperback
Dimensions
Item Length
92.5 in
Item Width
75 in
Additional Product Features
Intended Audience
Trade
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.31
Synopsis
Learn how to solve real-world data problems using machine learning and R Key Features: The 10th Anniversary Edition of the bestselling R machine learning book, updated with 50% new content for R 4.0.0 and beyond Harness the power of R to build flexible, effective, and transparent machine learning models Learn quickly with this clear, hands-on guide by machine learning expert Brett Lantz Book Description: Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Fourth Edition provides a hands-on, accessible, and readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need for data pre-processing, uncovering key insights, making new predictions, and visualizing your findings. This 10th Anniversary Edition features several new chapters that reflect the progress of ML in the last few years and help you build your data science skills and tackle more challenging problems, including making successful ML models and advanced data preparation, building better learners, and making use of big data. You'll also find updates to the classic R data science book to R 4.0.0 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Whether you're looking to take your first steps with R for machine learning or making sure your skills and knowledge are up to date, this is an unmissable read that will help you find powerful new insights in your data. What You Will Learn: Learn the end-to-end process of machine learning from raw data to implementation Classify important outcomes using nearest neighbor and Bayesian methods Predict future events using decision trees, rules, and support vector machines Forecast numeric data and estimate financial values using regression methods Model complex processes with artificial neural networks Prepare, transform, and clean data using the tidyverse Evaluate your models and improve their performance Connect R to SQL databases and emerging big data technologies such as Spark, Hadoop, H2O, and TensorFlow Who this book is for: This book is designed to help data scientists, actuaries, data analysts, financial analysts, social scientists, business and machine learning students, and any other practitioners who want a clear, accessible guide to machine learning with R. No R experience is required, although prior exposure to statistics and programming is helpful., Learn how to solve real-world data problems using machine learning and R.Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features The 10th Anniversary Edition of the bestselling R machine learning book, updated with 50% new content for R 4.0.0 and beyond Harness the power of R to build flexible, effective, and transparent machine learning models Learn quickly with this clear, hands-on guide by machine learning expert Brett Lantz Book Description Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data.Machine Learning with R, Fourth Edition, provides a hands-on, accessible, and readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to know for data pre-processing, uncovering key insights, making new predictions, and visualizing your findings. This 10th Anniversary Edition features several new chapters that reflect the progress of machine learning in the last few years and help you build your data science skills and tackle more challenging problems, including making successful machine learning models and advanced data preparation, building better learners, and making use of big data.You'll also find this classic R data science book updated to R 4.0.0 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Whether you're looking to take your first steps with R for machine learning or making sure your skills and knowledge are up to date, this is an unmissable read that will help you find powerful new insights in your data. What you will learn Learn the end-to-end process of machine learning from raw data to implementation Classify important outcomes using nearest neighbor and Bayesian methods Predict future events using decision trees, rules, and support vector machines Forecast numeric data and estimate financial values using regression methods Model complex processes with artificial neural networks Prepare, transform, and clean data using the tidyverse Evaluate your models and improve their performance Connect R to SQL databases and emerging big data technologies such as Spark, Hadoop, H2O, and TensorFlow Who this book is for This book is designed to help data scientists, actuaries, data analysts, financial analysts, social scientists, business and machine learning students, and any other practitioners who want a clear, accessible guide to machine learning with R. No R experience is required, although prior exposure to statistics and programming is helpful.]]>
LC Classification Number
Q325.5.L3 2023
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- 8***5 (18)- Feedback left by buyer.Past monthVerified purchaseI didn't see a verbal description of this book as "hardcover" or paperback. Cover design and price were similar to both cover styles. I thought I'd left a question for the seller, but I may have done something wrong. The package was too small to match the hardcovers previously received so I returned it unopened. Seller was very efficient, and packaging offered excellent protection. Haven't checked to see if refund was processed.
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- l***l (29)- Feedback left by buyer.Past yearVerified purchaseExcellent! This seller has really good prices, communication, packaging and fast shipping. The book I bought was better than described and I would definitely buy from this seller again. It was my time to have this book.🙌 A+++++El Kybalion by Trismegisto, Hermes, Like New Used, Free shipping in the US (#354955234211)
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