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Language: English
Published by Manning (edition First Edition), 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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Paperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
Language: English
Published by Manning Publications, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
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Paperback. Condition: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
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Condition: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.
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Language: English
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
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. pp. 400.
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Add to basketPAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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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 Pearson,, 2019
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Soft cover. Condition: New. ISBN:9781617295607.
Language: English
Published by Manning Publications, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
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Condition: New. 2019. Paperback. . . . . .
Language: English
Published by Manning Publications 2019-10-11, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
Seller: Chiron Media, Wallingford, United Kingdom
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Add to basketPaperback. Condition: New.
Language: English
Published by Manning Publications, 2019
ISBN 10: 1617295604 ISBN 13: 9781617295607
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Add to basketPaperback. 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.
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Paperback. Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-12 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.