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Mastering Machine Learning with R
Mastering Machine Learning with R

Mastering Machine Learning with R: Advanced prediction, algorithms, and learning methods with R 3.x , Second Edition

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Profile Icon Cory Lesmeister Profile Icon Doug Ortiz Profile Icon Vikram Dhillon Profile Icon Miroslav Kopecky
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$41.39 $45.99
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.8 (4 Ratings)
eBook Apr 2017 420 pages 2nd Edition
eBook
$41.39 $45.99
Paperback
$57.99
eBook + Subscription
$29.99 Monthly
Arrow left icon
Profile Icon Cory Lesmeister Profile Icon Doug Ortiz Profile Icon Vikram Dhillon Profile Icon Miroslav Kopecky
Arrow right icon
$41.39 $45.99
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.8 (4 Ratings)
eBook Apr 2017 420 pages 2nd Edition
eBook
$41.39 $45.99
Paperback
$57.99
eBook + Subscription
$29.99 Monthly
eBook
$41.39 $45.99
Paperback
$57.99
eBook + Subscription
$29.99 Monthly

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Mastering Machine Learning with R

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Key benefits

  • Understand and apply machine learning methods using an extensive set of R packages such as XGBOOST
  • Understand the benefits and potential pitfalls of using machine learning methods such as Multi-Class Classification and Unsupervised Learning
  • Implement advanced concepts in machine learning with this example-rich guide

Description

This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating Recommendation Engines; use multi-class classification and deep learning; and more. You will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. More than just knowing the outcome, you’ll understand how these concepts work and what they do. With a slow learning curve on topics such as neural networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets.

Who is this book for?

This book is for data science professionals, data analysts, or anyone with a working knowledge of machine learning, with R who now want to take their skills to the next level and become an expert in the field.

What you will learn

  • * Gain deep insights into the application of machine learning tools in 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
  • * Master fundamental learning methods such as linear and logistic regression
  • * Comprehend advanced learning methods such as support vector machines
  • * Learn how to use R in a cloud service such as Amazon

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Apr 24, 2017
Length: 420 pages
Edition : 2nd
Language : English
ISBN-13 : 9781787284487
Category :
Languages :

What do you get with eBook?

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Product feature icon Download this book in EPUB and PDF formats
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Product feature icon AI Assistant (beta) to help accelerate your learning
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Product Details

Publication date : Apr 24, 2017
Length: 420 pages
Edition : 2nd
Language : English
ISBN-13 : 9781787284487
Category :
Languages :

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Frequently bought together


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Total $ 205.97
Machine Learning with R Cookbook
$57.99
Mastering Machine Learning with R
$57.99
R: Predictive Analysis
$89.99
Total $ 205.97 Stars icon

Table of Contents

16 Chapters
A Process for Success Chevron down icon Chevron up icon
Linear Regression - The Blocking and Tackling of Machine Learning Chevron down icon Chevron up icon
Logistic Regression and Discriminant Analysis Chevron down icon Chevron up icon
Advanced Feature Selection in Linear Models Chevron down icon Chevron up icon
More Classification Techniques - K-Nearest Neighbors and Support Vector Machines Chevron down icon Chevron up icon
Classification and Regression Trees Chevron down icon Chevron up icon
Neural Networks and Deep Learning Chevron down icon Chevron up icon
Cluster Analysis Chevron down icon Chevron up icon
Principal Components Analysis Chevron down icon Chevron up icon
Market Basket Analysis, Recommendation Engines, and Sequential Analysis Chevron down icon Chevron up icon
Creating Ensembles and Multiclass Classification Chevron down icon Chevron up icon
Time Series and Causality Chevron down icon Chevron up icon
Text Mining Chevron down icon Chevron up icon
R on the Cloud Chevron down icon Chevron up icon
R Fundamentals Chevron down icon Chevron up icon
Sources Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.8
(4 Ratings)
5 star 0%
4 star 50%
3 star 0%
2 star 25%
1 star 25%
Bluebird Sep 03, 2017
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Yes the book is worth reading. The only con is black and white pic.. Which is not too bad.apart, the book is not for starters but for the people who what deep understanding of ML. It do not contain a to z but what ever it cover it is good
Amazon Verified review Amazon
Nick P Jan 31, 2018
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Highly recommend it to any student taking a finance or statics class.
Amazon Verified review Amazon
Amazon Customer May 24, 2017
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
The book was not up to the expectations. They used very cheap paper printing is not good and also some pages are not visible to read.Content wise is also not no real time data sets used all they used toy data sets no clear explanation also as the name says "Mastering" but its notI bought "Machine learning with r from Packt" publications.That was very good.setting the expectaions from packt i bought but it is not worth.
Amazon Verified review Amazon
Jose Luis Oct 05, 2017
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Sometimes, the code in the book doesn't work (R shows error messages and stop running the code) because the data doesn't meet the function requirements.Charts are duplicated / missed what makes not possible to follow the examples properly.This book can be used to get notions about the process but not not master ML with R unless you have R and stats knowledge that enables you to rewrite some code.I have been sending the erratas to the publisher without any respond so far.
Amazon Verified review Amazon
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