eBook - ePub

Data Science with Python and Dask

Name: Data Science with Python and Dask
ISBN: 9781638353546

Jesse Daniel,

296 pages
English
ePUB (mobile friendly)
Available on iOS & Android

eBook - ePub

Data Science with Python and Dask

Jesse Daniel,

About this book

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

About the Reader For data scientists and developers with experience using Python and the PyData stack. About the Author 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. Table of Contents

PART 1 - The Building Blocks of scalable computing

Why scalable computing matters
Introducing Dask

PART 2 - Working with Structured Data using Dask DataFrames

Introducing Dask DataFrames
Loading data into DataFrames
Cleaning and transforming DataFrames
Summarizing and analyzing DataFrames
Visualizing DataFrames with Seaborn
Visualizing location data with Datashader

PART 3 - Extending and deploying Dask

Working with Bags and Arrays
Machine learning with Dask-ML
Scaling and deploying Dask

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Yes, you can access Data Science with Python and Dask by Jesse Daniel in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.