{"product_id":"9781617299193","title":"Effective Data Science Infrastructure: How to make data scientists productive","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=\"\"\u003eTuulos, Ville\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\u003e8\/16\/2022\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\u003eSimplify data science infrastructure to give data scientists an efficient path from prototype to production.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eIn \u003ci\u003eEffective Data Science Infrastructure\u003c\/i\u003e you will learn how to:\u003cbr\u003e\u003cbr\u003eDesign data science infrastructure that boosts productivity\u003cbr\u003eHandle compute and orchestration in the cloud\u003cbr\u003eDeploy machine learning to production\u003cbr\u003eMonitor and manage performance and results\u003cbr\u003eCombine cloud-based tools into a cohesive data science environment\u003cbr\u003eDevelop reproducible data science projects using Metaflow, Conda, and Docker\u003cbr\u003eArchitect complex applications for multiple teams and large datasets\u003cbr\u003eCustomize and grow data science infrastructure\u003cbr\u003e\u003cbr\u003e\u003ci\u003eEffective Data Science Infrastructure: How to make data scientists more productive\u003c\/i\u003e is a hands-on guide to assembling infrastructure for data science and machine learning applications. It reveals the processes used at Netflix and other data-driven companies to manage their cutting edge data infrastructure. In it, you’ll master scalable techniques for data storage, computation, experiment tracking, and orchestration that are relevant to companies of all shapes and sizes. You’ll learn how you can make data scientists more productive with your existing cloud infrastructure, a stack of open source software, and idiomatic Python.\u003cbr\u003e\u003cbr\u003eThe author is donating proceeds from this book to charities that support women and underrepresented groups in data science.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the technology\u003c\/b\u003e\u003cbr\u003eGrowing data science projects from prototype to production requires reliable infrastructure. Using the powerful new techniques and tooling in this book, you can stand up an infrastructure stack that will scale with any organization, from startups to the largest enterprises.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the book\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eEffective Data Science Infrastructure\u003c\/i\u003e teaches you to build data pipelines and project workflows that will supercharge data scientists and their projects. Based on state-of-the-art tools and concepts that power data operations of Netflix, this book introduces a customizable cloud-based approach to model development and MLOps that you can easily adapt to your company’s specific needs. As you roll out these practical processes, your teams will produce better and faster results when applying data science and machine learning to a wide array of business problems.\u003cbr\u003e\u003cbr\u003eWhat's inside\u003cbr\u003e\u003cbr\u003eHandle compute and orchestration in the cloud\u003cbr\u003eCombine cloud-based tools into a cohesive data science environment\u003cbr\u003eDevelop reproducible data science projects using Metaflow, AWS, and the Python data ecosystem\u003cbr\u003eArchitect complex applications that require large datasets and models, and a team of data scientists\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the reader\u003c\/b\u003e\u003cbr\u003eFor infrastructure engineers and engineering-minded data scientists who are familiar with Python.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the author\u003c\/b\u003e\u003cbr\u003eAt Netflix, \u003cb\u003eVille Tuulos\u003c\/b\u003e designed and built Metaflow, a full-stack framework for data science. Currently, he is the CEO of a startup focusing on data science infrastructure.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1 Introducing data science infrastructure\u003cbr\u003e2 The toolchain of data science\u003cbr\u003e3 Introducing Metaflow\u003cbr\u003e4 Scaling with the compute layer\u003cbr\u003e5 Practicing scalability and performance\u003cbr\u003e6 Going to production\u003cbr\u003e7 Processing data\u003cbr\u003e8 Using and operating models\u003cbr\u003e9 Machine learning with the full stack","brand":"Manning","offers":[{"title":"Default Title","offer_id":45061756322047,"sku":"9781617299193","price":59.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0452\/0886\/2873\/files\/Jacket_720ddeda-0985-4e07-abd6-790d7f0f2334.jpg?v=1771351347","url":"https:\/\/massivebookshop.com\/products\/9781617299193","provider":"MASSIVE BOOKSHOP","version":"1.0","type":"link"}