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Mastering Predictive Analytics with R, Second Edition
Mastering Predictive Analytics with R, Second Edition

Mastering Predictive Analytics with R, Second Edition: Machine learning techniques for advanced models , Second Edition

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Profile Icon James D. Miller Profile Icon Rui Miguel Forte
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€22.99 €32.99
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
eBook Aug 2017 448 pages 2nd Edition
eBook
€22.99 €32.99
Paperback
€41.99
Subscription
Free Trial
Renews at €18.99p/m
Arrow left icon
Profile Icon James D. Miller Profile Icon Rui Miguel Forte
Arrow right icon
€22.99 €32.99
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
eBook Aug 2017 448 pages 2nd Edition
eBook
€22.99 €32.99
Paperback
€41.99
Subscription
Free Trial
Renews at €18.99p/m
eBook
€22.99 €32.99
Paperback
€41.99
Subscription
Free Trial
Renews at €18.99p/m

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Mastering Predictive Analytics with R, Second Edition

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Key benefits

  • • 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

Description

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 you train models that can handle really large datasets? This book will also show you just that. Finally, you will tackle the really important topic of deep learning by implementing applications on word embedding and recurrent neural networks. By the end of this book, you will have explored and tested the most popular modeling techniques in use on real- world datasets and mastered a diverse range of techniques in predictive analytics using R.

Who is this book 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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Aug 18, 2017
Length: 448 pages
Edition : 2nd
Language : English
ISBN-13 : 9781787124356
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Product Details

Publication date : Aug 18, 2017
Length: 448 pages
Edition : 2nd
Language : English
ISBN-13 : 9781787124356
Category :
Languages :
Concepts :

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Frequently bought together


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Total 120.97
Mastering Machine Learning with R, Second Edition
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Mastering Predictive Analytics with R, Second Edition
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Total 120.97 Stars icon

Table of Contents

15 Chapters
1. Gearing Up for Predictive Modeling Chevron down icon Chevron up icon
2. Tidying Data and Measuring Performance Chevron down icon Chevron up icon
3. Linear Regression Chevron down icon Chevron up icon
4. Generalized Linear Models Chevron down icon Chevron up icon
5. Neural Networks Chevron down icon Chevron up icon
6. Support Vector Machines Chevron down icon Chevron up icon
7. Tree-Based Methods Chevron down icon Chevron up icon
8. Dimensionality Reduction Chevron down icon Chevron up icon
9. Ensemble Methods Chevron down icon Chevron up icon
10. Probabilistic Graphical Models Chevron down icon Chevron up icon
11. Topic Modeling Chevron down icon Chevron up icon
12. Recommendation Systems Chevron down icon Chevron up icon
13. Scaling Up Chevron down icon Chevron up icon
14. Deep Learning Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

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Full star icon Full star icon Full star icon Full star icon Full star icon 5
(1 Ratings)
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1 star 0%
Amazon Customer Dec 31, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book provides hands on learning experience. If you want to master the theoretical underpinnings of predictive modeling, then this is not for you. Rather, if you want to able to build predictive models right from day 1 regardless of your background, then I strongly recommend this book. This is the best book on predictive modeling in R so far.
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