Data Science with Python and Dask pdf epub mobi txt 電子書下載2025

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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.

出版者:Manning Publications

作者:Jesse Daniel

出品人:

頁數:296

译者:

出版時間:2019-7-30

價格:USD 49.99

裝幀:Paperback

isbn號碼:9781617295607

叢書系列:

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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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