Atsiliepimai
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This hands-on 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 whether you re on Windows, OS X, or Linux author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.
Discover why the command line is an agile, scalable, and extensible technology. Even if you re already comfortable processing data with, say, Python or R, you ll greatly improve your data science workflow by also leveraging the power of the command line.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on plain text, CSV, HTML/XML, and JSONExplore data, compute descriptive statistics, and create visualizationsManage your data science workflow using DrakeCreate reusable tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelines using GNU ParallelModel data with dimensionality reduction, clustering, regression, and classification algorithms"
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This hands-on 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 whether you re on Windows, OS X, or Linux author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.
Discover why the command line is an agile, scalable, and extensible technology. Even if you re already comfortable processing data with, say, Python or R, you ll greatly improve your data science workflow by also leveraging the power of the command line.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on plain text, CSV, HTML/XML, and JSONExplore data, compute descriptive statistics, and create visualizationsManage your data science workflow using DrakeCreate reusable tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelines using GNU ParallelModel data with dimensionality reduction, clustering, regression, and classification algorithms"
Atsiliepimai