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Published by Manning Publications, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
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Language: English
Published by Manning Publications, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
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Published by Manning Publications, US, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
Seller: Rarewaves USA, OSWEGO, IL, U.S.A.
Paperback. Condition: New. Large datasets tend to be distributed, non-uniform, and prone to change. Dask simplifies the process of ingesting, filtering, and transforming data, reducing or eliminating the need for a heavyweight framework like Spark. Data Science at Scale with Python and Dask teaches readers how to build distributed data projects that can handle huge amounts of data. The book introduces Dask Data Frames and teaches helpful code patterns to streamline the reader's analysis. Key Features Working with large structured datasets Writing DataFrames Cleaningand visualizing DataFrames Machine learning with Dask-ML Working with Bags and Arrays Written for data engineers and scientists with experience using Python. Knowledge of the PyData stack (Pandas, NumPy, and Scikit-learn) will be helpful. No experience with low-level parallelism is required. About the technology Dask is a self-contained, easily extendible library designed to query, stream, filter, and consolidate huge datasets. Jesse Daniel has five years of experience writing applications in Python, including three years working with in the PyData stack (Pandas, NumPy, SciPy, Scikit-Learn). Jesse joined the faculty of the University of Denver in 2016 as an adjunct professor of business information and analytics, where he currently teaches a Python for Data Science course.
Language: English
Published by Manning Publications Company, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. 400.
Language: English
Published by Manning Publications Company, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
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Language: English
Published by Manning Publications Company, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
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Condition: New. pp. 400.
Language: English
Published by Manning Publications, New York, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condition: new. Paperback. Large datasets tend to be distributed, non-uniform, and prone to change. Dask simplifies the process of ingesting, filtering, and transforming data, reducing or eliminating the need for a heavyweight framework like Spark. Data Science at Scale with Python and Dask teaches readers how to build distributed data projects that can handle huge amounts of data. The book introduces Dask Data Frames and teaches helpful code patterns to streamline the readers analysis. Key Features Working with large structured datasets Writing DataFrames Cleaningand visualizing DataFrames Machine learning with Dask-ML Working with Bags and Arrays Written for data engineers and scientists with experience using Python. Knowledge of the PyData stack (Pandas, NumPy, and Scikit-learn) will be helpful. No experience with low-level parallelism is required. About the technology Dask is a self-contained, easily extendible library designed to query, stream, filter, and consolidate huge datasets. Jesse Daniel has five years of experience writing applications in Python, including three years working with in the PyData stack (Pandas, NumPy, SciPy, Scikit-Learn). Jesse joined the faculty of the University of Denver in 2016 as an adjunct professor of business information and analytics, where he currently teaches a Python for Data Science course. Large datasets tend to be distributed, non-uniform, and prone to change. Teaching readers how to build distributed data projects that can handle huge amounts of data, this edition introduces Dask DataFrames and teaches helpful code patterns to streamline the reader's analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Language: English
Published by Manning Publications, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
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Language: English
Published by Manning Publications 2019-10-11, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
Seller: Chiron Media, Wallingford, United Kingdom
Paperback. Condition: New.
Language: English
Published by Manning Publications, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
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Paperback. Condition: Brand New. pap/psc edition. 276 pages. 9.00x7.25x0.50 inches. In Stock.
Language: English
Published by Manning Publications, US, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
Seller: Rarewaves USA United, OSWEGO, IL, U.S.A.
Paperback. Condition: New. Large datasets tend to be distributed, non-uniform, and prone to change. Dask simplifies the process of ingesting, filtering, and transforming data, reducing or eliminating the need for a heavyweight framework like Spark. Data Science at Scale with Python and Dask teaches readers how to build distributed data projects that can handle huge amounts of data. The book introduces Dask Data Frames and teaches helpful code patterns to streamline the reader's analysis. Key Features Working with large structured datasets Writing DataFrames Cleaningand visualizing DataFrames Machine learning with Dask-ML Working with Bags and Arrays Written for data engineers and scientists with experience using Python. Knowledge of the PyData stack (Pandas, NumPy, and Scikit-learn) will be helpful. No experience with low-level parallelism is required. About the technology Dask is a self-contained, easily extendible library designed to query, stream, filter, and consolidate huge datasets. Jesse Daniel has five years of experience writing applications in Python, including three years working with in the PyData stack (Pandas, NumPy, SciPy, Scikit-Learn). Jesse joined the faculty of the University of Denver in 2016 as an adjunct professor of business information and analytics, where he currently teaches a Python for Data Science course.