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