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- Author: Nishant Shukla
- Publisher: Packt Publishing
- Year: 2014
- Pages: 288
- ISBN-10: 1783286334
- ISBN-13: 9781783286331
- Format: 19.1 x 23.5 x 1.8 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
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Description
Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes.
This book will take you on a voyage through all the steps involved in data analysis. It provides synergy between Haskell and data modeling, consisting of carefully chosen examples featuring some of the most popular machine learning techniques.
You will begin with how to obtain and clean data from various sources. You will then learn how to use various data structures such as trees and graphs. The meat of data analysis occurs in the topics involving statistical techniques, parallelism, concurrency, and machine learning algorithms, along with various examples of visualizing and exporting results. By the end of the book, you will be empowered with techniques to maximize your potential when using Haskell for data analysis.
EXTRA 10 % discount with code: EXTRA
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The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Nishant Shukla
- Publisher: Packt Publishing
- Year: 2014
- Pages: 288
- ISBN-10: 1783286334
- ISBN-13: 9781783286331
- Format: 19.1 x 23.5 x 1.8 cm, softcover
- Language: English English
Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes.
This book will take you on a voyage through all the steps involved in data analysis. It provides synergy between Haskell and data modeling, consisting of carefully chosen examples featuring some of the most popular machine learning techniques.
You will begin with how to obtain and clean data from various sources. You will then learn how to use various data structures such as trees and graphs. The meat of data analysis occurs in the topics involving statistical techniques, parallelism, concurrency, and machine learning algorithms, along with various examples of visualizing and exporting results. By the end of the book, you will be empowered with techniques to maximize your potential when using Haskell for data analysis.
Reviews