Put your Haskell skills to work and generate publication-ready visualizations in no time at all
About This Video
Perform meaningful analysis on real-world data in the Haskell language while utilizing the IHaskell environment for Jupyter notebooks.
Create publication-ready visualizations of data.
Understand the mathematics behind simple data analysis procedures.
We use a gentle introduction to the mathematics behind data analysis.
Data analysis is part computer science and part statistics. An important part of data analysis is validating your assumptions with real-world data to see if there is a pattern, or a particular user behavior that you can validate. This video course will help you get up to speed with the basics of data analysis and approaches in the Haskell language. You'll learn about statistical computing, file formats (CSV and SQLite3), descriptive statistics, charts, and onto more advanced concepts like understanding the importance of normal distribution. Whilst mathematics is a big part of data analysis, we’ve tried to keep this course simple and approachable so that you can apply what you learn to the real world.
Downloading the example code for this course: You can download the example code files for this course on GitHub at the following link: https://github.com/PacktPublishing/Getting-Started-with-Haskell-Data-Analysis-Video-. If you require support please email: firstname.lastname@example.org
Table of contents
- Chapter 1 : Descriptive Statistics
- Chapter 2 : SQLite3
- Chapter 3 : Regular Expressions
- Chapter 4 : Visualizations
- Chapter 5 : Kernel Density Estimation
- Chapter 6 : Course Review
- Title: Getting Started with Haskell Data Analysis
- Release date: July 2016
- Publisher(s): Packt Publishing
- ISBN: 9781785880841
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