Data Science with Python and Dask 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Data Science with Python and Dask

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Jesse Daniel 作者
Manning Publications
譯者
2019-7-30 出版日期
296 頁數
USD 49.99 價格
Paperback
叢書系列
9781617295607 圖書編碼

Data Science with Python and Dask 在線電子書 圖書標籤: Python  計算機  軟件工程  計算機科學  機器學習  數據分析  AI  2019   


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Data Science with Python and Dask 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Data Science with Python and Dask 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Data Science with Python and Dask 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Data Science with Python and Dask 在線電子書 著者簡介

Jesse Daniel is an experienced Python developer. He taught Python for Data Science at the University of Denver and leads a team of data scientists at a Denver-based media technology company.


Data Science with Python and Dask 在線電子書 著者簡介


Data Science with Python and Dask 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Data Science with Python and Dask 在線電子書 圖書描述

Summary

Dask is a native parallel analytics tool designed to integrate seamlessly with the libraries you're already using, including Pandas, NumPy, and Scikit-Learn. With Dask you can crunch and work with huge datasets, using the tools you already have. And Data Science with Python and Dask is your guide to using Dask for your data projects without changing the way you work!

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. You'll find registration instructions inside the print book.

About the Technology

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.

About the Book

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.

What's inside

Working with large, structured and unstructured datasets

Visualization with Seaborn and Datashader

Implementing your own algorithms

Building distributed apps with Dask Distributed

Packaging and deploying Dask apps

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