Data Science at the Command Line (el. knyga) (skaityta knyga) | knygos.lt

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In this practical guide, you’ll learn how to leverage the power of the command line for doing data science. By combining small, yet powerful, command-line tools, you can quickly obtain, scrub, explore, and model your data. Even if you’re already comfortable processing data with R or Python, being able to integrate the command line into your existing workflow will make you a more efficient and productive data scientist.

Learn essential concepts and built-in commands of the *nix command line
Get started with your own Data Science Toolbox on either Linux, Mac OS X, or Microsoft Windows
Use classic command-line tools such as grep, sed, and awk
Obtain data from websites, APIs, databases, and spreadsheets
Parallelize and distribute data-intensive pipelines to remote machines, including AWS EC2
Clean data in CSV, JSON, and XML/HTML formats using csvkit, and jq, and scrape
Apply dimensionality reduction, clustering, regression, and classification algorithms
Visualize data and results from the command line using gnuplot and ggplot
Turn Bash one-liners and existing Python and R code into reusable command-line tools