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.
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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. Currently, Jeroen is the CEO of Data Science Workshops, which organises open enrollment workshops, in-company courses, inspiration sessions, hackathons, and meetups. All related to data science of course. He lives with his wife and two kids in Rotterdam, the Netherlands.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : New. 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 80 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, and engineers; software and machine learning engineers; and system administrators.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on text, CSV, HTM, XML, and JSON filesExplore data, compute descriptive statistics, and create visualizationsManage your data science workflowCreate reusable command-line tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelinesModel data with dimensionality reduction, clustering, regression, and classification algorithms. N° de réf. du vendeur LU-9781492087915
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Paperback. Etat : new. Paperback. 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 80 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, and engineers; software and machine learning engineers; and system administrators.Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on text, CSV, HTM, XML, and JSON files Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow Create reusable command-line tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines Model data with dimensionality reduction, clustering, regression, and classification algorithms" 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781492087915
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Paperback. Etat : New. 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 80 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, and engineers; software and machine learning engineers; and system administrators.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on text, CSV, HTM, XML, and JSON filesExplore data, compute descriptive statistics, and create visualizationsManage your data science workflowCreate reusable command-line tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelinesModel data with dimensionality reduction, clustering, regression, and classification algorithms. N° de réf. du vendeur LU-9781492087915
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