Data Science at the Command Line 2nd Edition
This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data.
To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools—useful whether you work with Windows, macOS, or Linux.You’ll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you’re comfortable processing data with Python or R, you’ll learn how to greatly improve your data science workflow by leveraging the command line’s power. This book is ideal for data scientists, analysts, engineers, system administrators, and researchers.
- Obtain data from websites, APIs, databases, and spreadsheets
- Perform scrub operations on text, CSV, HTML, XML, and JSON files
- Explore data, compute descriptive statistics, and create visualizations
- Manage your data science workflow
- Create your own tools from one-liners and existing Python or R code
- Parallelize and distribute data-intensive pipelines
- Model data with dimensionality reduction, regression, and classification algorithms
- Leverage the command line from Python, Jupyter, R, RStudio, and Apache Spark
About the Author
Jeroen Janssens teaches data science; often through training and coaching, occasionally through speaking, and infrequently through writing. His interests include visualizing data, building machine learning models, and automating things using either Python, R, or Bash. He is the author of Data Science at the Command Line, published by O’Reilly Media. Jeroen holds a PhD in machine learning from Tilburg University and an MSc in artificial intelligence from Maastricht University. Previously, he was an assistant professor at Jheronimus Academy of Data Science and a data scientist at Elsevier in Amsterdam and various startups in New York City.
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