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Haskell Data Analysis cookbook Cover

Haskell Data Analysis cookbook

Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes

Paid access
|Sep 2025
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Key Features

    Book Description

    Step-by-step recipes filled with practical code samples and engaging examples demonstrate Haskell in practice, and then the concepts behind the code.
    This book shows functional developers and analysts how to leverage their existing knowledge of Haskell specifically for high-quality data analysis. A good understanding of data sets and functional programming is assumed.

    What you will learn

    • Obtain and analyze raw data from various sources including text files, CSV files, databases, and websites
    • Implement practical tree and graph algorithms on various datasets
    • Apply statistical methods such as moving average and linear regression to understand patterns
    • Fiddle with parallel and concurrent code to speed up and simplify timeconsuming algorithms
    • Find clusters in data using some of the most popular machine learning algorithms
    • Manage results by visualizing or exporting data

    Who this book is for

    Table of Contents

    1. Obtaining Data
    2. Cleaning Data
    3. String Manipulations
    4. Hashing Data
    5. Tree Data Structure
    6. Graph Data Structure
    7. Statistical Methods
    8. Clustering
    9. Parallel Design
    10. Real Time Data Analysis
    11. Visualizing Data
    12. Evoking External Programs
    PDF ISBN: 978-1-78328-634-8
    Publisher: Packt Publishing Limited
    Copyright owner: © 2014 Packt Publishing Limited
    Publication date: 2025
    Language: English
    Pages: 334