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Haskell Data Analysis cookbook

You're reading from   Haskell Data Analysis cookbook Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes

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Product type Paperback
Published in Jun 2014
Publisher
ISBN-13 9781783286331
Length 334 pages
Edition 1st Edition
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Author (1):
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Nishant Shukla Nishant Shukla
Author Profile Icon Nishant Shukla
Nishant Shukla
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Toc

Table of Contents (14) Chapters Close

Preface 1. The Hunt for Data FREE CHAPTER 2. Integrity and Inspection 3. The Science of Words 4. Data Hashing 5. The Dance with Trees 6. Graph Fundamentals 7. Statistics and Analysis 8. Clustering and Classification 9. Parallel and Concurrent Design 10. Real-time Data 11. Visualizing Data 12. Exporting and Presenting Index

Introduction


Many interesting analysis techniques can be used on a large corpus of words. Whether it be examining the structure of a sentence or the content of a book, these recipes will introduce us to some useful tools.

When manipulating strings for data analysis, some of the most common functions are among substring search and edit distance computations. Since numbers are often found in a corpus of text, this chapter will start by showing how to represent numbers in an arbitrary base as a string. We will cover a couple of string-searching algorithms and then focus on extracting text to study not only the words but also how the words are used together.

Many practical applications can be constructed given the simple set of tools provided in this section. For example, in the last recipe, we will demonstrate a way to correct spelling mistakes. How we use these algorithms is entirely up to our creativity, but at least having them at our disposal is an excellent start.

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