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Hands-On Data Science with R

You're reading from   Hands-On Data Science with R Techniques to perform data manipulation and mining to build smart analytical models using R

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789139402
Length 420 pages
Edition 1st Edition
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Authors (4):
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Nataraj Dasgupta Nataraj Dasgupta
Author Profile Icon Nataraj Dasgupta
Nataraj Dasgupta
Vitor Bianchi Lanzetta Vitor Bianchi Lanzetta
Author Profile Icon Vitor Bianchi Lanzetta
Vitor Bianchi Lanzetta
Doug Ortiz Doug Ortiz
Author Profile Icon Doug Ortiz
Doug Ortiz
Ricardo Anjoleto Farias Ricardo Anjoleto Farias
Author Profile Icon Ricardo Anjoleto Farias
Ricardo Anjoleto Farias
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Table of Contents (16) Chapters Close

Preface 1. Getting Started with Data Science and R FREE CHAPTER 2. Descriptive and Inferential Statistics 3. Data Wrangling with R 4. KDD, Data Mining, and Text Mining 5. Data Analysis with R 6. Machine Learning with R 7. Forecasting and ML App with R 8. Neural Networks and Deep Learning 9. Markovian in R 10. Visualizing Data 11. Going to Production with R 12. Large Scale Data Analytics with Hadoop 13. R on Cloud 14. The Road Ahead 15. Other Books You May Enjoy

Cloud computing

From my first year as an undergraduate student, there was this story a professor told us about top-notch computers taking weeks to fit a single linear regression model, back in her days as an undergrad student. I recall thinking, It's lucky that today's computers can run it in no time. This was naive though. As the history of computing shows, every time a faster horse is born, a more challenging track is built.

Computers have advanced a lot and so have the models—thankfully. In addition, our capacity to gather data has improved by teraflops. The first time I felt the need for cloud computing, I had designed a model so huge that I couldn't load it and the data simultaneously. It was either one or the other. Using a cloud service, this problem became manageable.

Using distributed computing solutions, such as Hadoop and Spark, is another way...
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