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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

Product type Paperback

Published in Jun 2014

Publisher

ISBN-13 9781783286331

Length 334 pages

Edition 1st Edition

Languages

Haskell

Concepts

Data Analysis

Author (1):

Nishant Shukla

View More author details

Table of Contents (14) Chapters

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

Chapter 9. Parallel and Concurrent Design

In this chapter, we will cover the following recipes:

Using the Haskell Runtime System (RTS) options
Evaluating a procedure in parallel
Controlling parallel algorithms in sequence
Forking I/O actions for concurrency
Communicating with a forked I/O action
Killing forked threads
Parallelizing pure functions using the Par monad
Mapping over a list in parallel
Accessing tuple elements in parallel
Implementing MapReduce to count word frequencies
Manipulating images in parallel using Repa
Benchmarking runtime performance in Haskell
Using the criterion package to measure performance
Benchmarking runtime performance in the terminal

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Programming languages

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Authors (1)

Nishant Shukla

Nishant Shukla

Nishant Shukla is a computer scientist with a passion for mathematics. Throughout the years, he has worked for a handful of start-ups and large corporations including WillowTree Apps, Microsoft, Facebook, and Foursquare. Stepping into the world of Haskell was his excuse for better understanding Category Theory at first, but eventually, he found himself immersed in the language. His semester-long introductory Haskell course in the engineering school at the University of Virginia (http://shuklan.com/haskell) has been accessed by individuals from over 154 countries around the world, gathering over 45,000 unique visitors. Besides Haskell, he is a proponent of decentralized Internet and open source software. His academic research in the fields of Machine Learning, Neural Networks, and Computer Vision aim to supply a fundamental contribution to the world of computing.

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