Haskell-Data-Analysis-Cookbook/README.md

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# Haskell-Data-Analysis-Cookbook
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This is the accompanying source code for [Haskell Data Analysis Cookbook](http://haskelldata.com).
The latest source code is available on GitHub: https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook
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# Summary
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### [Chapter 1](/Ch01/README.md)
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*The Hunt for Data*, identifies core approaches in reading data from various external sources such as **CSV**, **JSON**, **XML**, **HTML**, **MongoDB**, and **SQLite**.
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### [Chapter 2](/Ch02/README.md)
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*Integrity and Inspection*, explains the importance of cleaning data through recipes about **trimming whitespace**, **lexing**, and **regular expression matching**.
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### [Chapter 3](/Ch03/README.md)
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*The Science of Words*, introduces common string manipulation algorithms including **base conversions**, **substring matching**, and **computing the edit distance**.
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### [Chapter 4](/Ch04/README.md)
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*Data Hashing*, covers essential hashing functions such as **MD5**, **SHA256**, **GeoHashing**, and **perceptual hashing**.
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### [Chapter 5](/Ch05/README.md)
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*A Dance with Trees*, establishes an understanding of the tree data structure through examples including **tree traversals**, **balancing trees**, and **Huffman coding**.
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### [Chapter 6](/Ch06/README.md)
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*Graph Fundamentals*, manifests rudimentary algorithms for graphical networks such as **graph traversals**, **visualization**, and **maximal clique detection**.
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### [Chapter 7](/Ch07/README.md)
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*Statistics and Analysis*, begins the investigation of important data analysis techniques encompassing **regression algorithms**, **Bayesian networks**, and **neural networks**.
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### [Chapter 8](/Ch08/README.md)
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*Clustering and Classification*, involves quintessential analysis methods involving **k-means clustering**, **hierarchical clustering**, **constructing decision trees**, and **implementing the k-Nearest Neighbors classifier**.
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### [Chapter 9](/Ch09/README.md)
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*Parallel and Concurrent Design*, introduces advance topics in Haskell such as **forking IO actions**, **mapping over lists in parallel**, and **benchmarking performance**.
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### [Chapter 10](/Ch10/README.md)
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*Real-time Fugue*, incorporates streamed data interactions from **Twitter**, **Internet Relay Chat (IRC)**, and **sockets**.
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### [Chapter 11](/Ch11/README.md)
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*Stunning Visuals*, comprises of sundry approaches to plotting graphs including **line charts**, **bar graphs**, **scatter plots**, and **D3.js visualizations**.
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### [Chapter 12](/Ch12/README.md)
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*The Final Exporting*, concludes the book with an enumeration of algorithms for exporting data to **CSV**, **JSON**, **HTML**, **MongoDB**, and **SQLite**.
# Artwork Attribution
Illustrations by [Lonku](http://lonku.tumblr.com/).