{"product_id":"9781617295607","title":"Data Science with Python and Dask","description":"\u003ctable\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eAuthor\/Contributor(s):\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003eDaniel, Jesse\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003ePublisher:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eManning\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eDate:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e7\/30\/2019\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eBinding:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003ePaperback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003eNEW\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\u003cb\u003eSummary\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eDask 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 \u003ci\u003eData Science with Python and Dask\u003c\/i\u003e is your guide to using Dask for your data projects without changing the way you work!\u003cbr\u003e\u003cbr\u003eYou'll find registration instructions inside the print book.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Technology\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eAn 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Book\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\u003ci\u003eData Science with Python and Dask\u003c\/i\u003e 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eWhat's inside\u003c\/b\u003e\u003cul\u003e\n\u003cli\u003eWorking with large, structured and unstructured datasets\u003c\/li\u003e\n\u003cli\u003eVisualization with Seaborn and Datashader\u003c\/li\u003e\n\u003cli\u003eImplementing your own algorithms\u003c\/li\u003e\n\u003cli\u003eBuilding distributed apps with Dask Distributed\u003c\/li\u003e\n\u003cli\u003ePackaging and deploying Dask apps\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003e\u003cb\u003eAbout the Reader\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eFor data scientists and developers with experience using Python and the PyData stack.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eJesse Daniel\u003c\/b\u003e 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\u003col\u003ePART 1 - The Building Blocks of scalable computing\u003cli\u003eWhy scalable computing matters \u003c\/li\u003e\n\u003cli\u003eIntroducing Dask \u003c\/li\u003ePART 2 - Working with Structured Data using Dask DataFrames \u003cli\u003eIntroducing Dask DataFrames \u003c\/li\u003e\n\u003cli\u003eLoading data into DataFrames \u003c\/li\u003e\n\u003cli\u003eCleaning and transforming DataFrames \u003c\/li\u003e\n\u003cli\u003eSummarizing and analyzing DataFrames \u003c\/li\u003e\n\u003cli\u003eVisualizing DataFrames with Seaborn \u003c\/li\u003e\n\u003cli\u003eVisualizing location data with Datashader \u003c\/li\u003ePART 3 - Extending and deploying Dask\u003cli\u003eWorking with Bags and Arrays \u003c\/li\u003e\n\u003cli\u003eMachine learning with Dask-ML \u003c\/li\u003e\n\u003cli\u003eScaling and deploying Dask \u003c\/li\u003e\n\u003c\/ol\u003e","brand":"Manning","offers":[{"title":"Default Title","offer_id":49088930349311,"sku":"9781617295607","price":49.99,"currency_code":"USD","in_stock":false}],"url":"https:\/\/massivebookshop.com\/de\/products\/9781617295607","provider":"MASSIVE BOOKSHOP","version":"1.0","type":"link"}