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Author Daniel, Jesse C., author.

Title Data science with Python and Dask / Jesse C. Daniel.

Publication Info. Shelter Island, NY : Manning Publications Co., [2019]
©2019
Location Call No. Status
 95th Street Adult Nonfiction  006.312 DAN 2019    DUE 02-08-21
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Description xvii, 276 pages : illustrations ; 24 cm
Note Includes index.
Summary An efficient data pipeline means everything for the success of a data science project. Dask is a flexible library for parallel computing in Python that makes it easy to build intuitive workflows for ingesting and analyzing large, distributed datasets. Dask provides dynamic task scheduling and parallel collections that extend the functionality of NumPy, Pandas, and Scikit-learn, enabling users to scale their code from a single laptop to a cluster of hundreds of machines with ease. "Data science with Python and Dask" teaches you to build scalable projects that can handle massive datasets. After meeting the Dask framework, you'll analyze data in the nYC Parking Ticket database and use DataFrames to streamline your process. Then, you'll create machine learning models using Dask-ML, build interactive visualizations, and build clusters using AWS and Docker.
Subject Big data.
Machine learning.
Python (Computer program language)
Information storage and retrieval systems -- Scalability.
Data mining.
ISBN 9781617295607 (pbk.)
1617295604 (pbk.)
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