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Getting Started with Haskell Data Analysis - Put your data analysis techniques to work and generate publication-ready visualizations (Paperback)
Loot Price: R661
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Getting Started with Haskell Data Analysis - Put your data analysis techniques to work and generate publication-ready visualizations (Paperback)
Expected to ship within 10 - 15 working days
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Put your Haskell skills to work and generate publication-ready
visualizations in no time at all Key Features Take your data
analysis skills to the next level using the power of Haskell
Understand regression analysis, perform multivariate regression,
and untangle different cluster varieties Create publication-ready
visualizations of data Book DescriptionEvery business and
organization that collects data is capable of tapping into its own
data to gain insights how to improve. Haskell is a purely
functional and lazy programming language, well-suited to handling
large data analysis problems. This book will take you through the
more difficult problems of data analysis in a hands-on manner. This
book 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 progress to more advanced concepts such as
understanding the importance of normal distribution. While
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. By the end of this book, you will have a
thorough understanding of data analysis, and the different ways of
analyzing data. You will have a mastery of all the tools and
techniques in Haskell for effective data analysis. What you will
learn Learn to parse a CSV file and read data into the Haskell
environment Create Haskell functions for common descriptive
statistics functions Create an SQLite3 database using an existing
CSV file Learn the versatility of SELECT queries for slicing data
into smaller chunks Apply regular expressions in large-scale
datasets using both CSV and SQLite3 files Create a Kernel Density
Estimator visualization using normal distribution Who this book is
forThis book is intended for people who wish to expand their
knowledge of statistics and data analysis via real-world examples.
A basic understanding of the Haskell language is expected. If you
are feeling brave, you can jump right into the functional
programming style.
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