Python Tools for Data Scientists: Pocket Primer
- 3h 44m
- Oswald Campesato
- Mercury Learning
- 2022
As part of the best-selling Pocket Primer series, this book is designed to provide a thorough introduction to numerous Python tools for data scientists. The book covers features of NumPy and Pandas, how to write regular expressions, and how to perform data cleaning tasks. It includes separate chapters on data visualization and working with Sklearn and SciPy. Companion files with source code are available.
FEATURES:
- Introduces Python, NumPy, Sklearn, SciPy, and awk
- Covers data cleaning tasks and data visualization
- Features numerous code samples throughout
- Includes companion files with source code
About the Author
Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, TensorFlow, and NLP. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the NLP Using R Pocket Primer (all Mercury Learning and Information).
In this Book
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Introduction to Python
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Introduction to NumPy
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Introduction to Pandas
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Working with Sklearn and Scipy
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Data Cleaning Tasks
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Data Visualization
