DevOps for Data Science by Alex Gold Hardcover Book

Description: DevOps for Data Science by Alex Gold Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description Data Scientists are experts at analyzing, modelling and visualizing data but, at one point or another, have all encountered difficulties in collaborating with or delivering their work to the people and systems that matter. Publisher Description Data Scientists are experts at analyzing, modelling and visualizing data but, at one point or another, have all encountered difficulties in collaborating with or delivering their work to the people and systems that matter. Born out of the agile software movement, DevOps is a set of practices, principles and tools that help software engineers reliably deploy work to production. This book takes the lessons of DevOps and aplies them to creating and delivering production-grade data science projects in Python and R.This books first section explores how to build data science projects that deploy to production with no frills or fuss. Its second section covers the rudiments of administering a server, including Linux, application, and network administration before concluding with a demystification of the concerns of enterprise IT/Administration in its final section, making it possible for data scientists to communicate and collaborate with their organizations security, networking, and administration teams.Key Features:• Start-to-finish labs take readers through creating projects that meet DevOps best practices and creating a server-based environment to work on and deploy them.• Provides an appendix of cheatsheets so that readers will never be without the reference they need to remember a Git, Docker, or Command Line command.• Distills what a data scientist needs to know about Docker, APIs, CI/CD, Linux, DNS, SSL, HTTP, Auth, and more.• Written specifically to address the concern of a data scientist who wants to take their Python or R work to production.There are countless books on creating data science work that is correct. This book, on the otherhand, aims to go beyond this, targeted at data scientists who want their work to be than merely accurate and deliver work that matters. Author Biography Alex leads the Solutions Engineering team at Posit (formerly RStudio). In that role, he has advised hundreds of organizations of all sizes and levels of sophistication to create production-grade open-source data science environments. Before coming to Posit, he was a data scientist and data science team lead and worked on politics, consulting, and healthcare. Details ISBN 1032100346 ISBN-13 9781032100340 Title DevOps for Data Science Author Alex Gold Format Hardcover Year 2024 Pages 256 Publisher Taylor & Francis Ltd GE_Item_ID:160232600; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

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End Time: 2024-10-27T04:05:46.000Z

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