Learning Haskell for Data Analysis
Learning Haskell for Data Analysis is an Intermediate level course on Developer, compiled by the author, James Church. This course is an important foundation for a person who needs to sharpen his/her Developer talent. It provides you a thorough grip on Developer, Programming Languages, Haskell, Developer, Programming Languages and Haskell.
Data is frequently available in raw form and in massive quantities, so knowing how to find the data you need and analyze it is crucial to being a successful data analyst. This course shows how to use Haskell for your data science needs. Instructor James Church first explains descriptive statistics, so you can discover the importance of ranges, means, medians, and standard deviations. Then, James gets you started with using SQLite3 so you can query data. Next, he takes you through working with regular expressions and visualizations. Finally, he discusses the topic of distribution by covering Kernel Density Estimation.
Note: This course was created by Packt Publishing. We are pleased to host this training in our library.
- Data ranges, means, and medians
- Standard deviation
- SQLite3 command line
- Slices of data
- Regular expressions
- Atoms and modifiers
- Character classes
- Line plots of a single variable
- Plotting a moving average
- Feature scaling
- Scatter plots
- Normal distribution
- Kernel density estimation (KDE)