{"product_id":"9781484230114","title":"Docker for Data Science: Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server","description":"\u003ch1\u003eDocker for Data Science: Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server\u003c\/h1\u003e \u003ch2\u003eCook, Joshua\u003c\/h2\u003e \u003cp\u003e\u003c\/p\u003e\u003cdiv\u003eLearn Docker \"infrastructure as code\" technology to define a system for performing standard but non-trivial data tasks on medium- to large-scale data sets, using Jupyter as the master controller.\u003c\/div\u003e\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\u003cdiv\u003eIt is not uncommon for a real-world data set to fail to be easily managed. The set may not fit well into access memory or may require prohibitively long processing. These are significant challenges to skilled software engineers and they can render the standard Jupyter system unusable. \u003cbr\u003e\n\u003c\/div\u003e\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\u003cdiv\u003eAs a solution to this problem, \u003ci\u003eDocker for Data Science\u003c\/i\u003e proposes using Docker. You will learn how to use existing pre-compiled public images created by the major open-source technologies—Python, Jupyter, Postgres—as well as using the Dockerfile to extend these images to suit your specific purposes. The Docker-Compose technology is examined and you will learn how it can be used to build a linked system with Python churning data behind the scenesand Jupyter managing these background tasks. Best practices in using existing images are explored as well as developing your own images to deploy state-of-the-art machine learning and optimization algorithms.\u003c\/div\u003e\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\u003cdiv\u003e\n\u003cdiv\u003e\u003cb\u003eWhat  You'll Learn \u003c\/b\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cul\u003e\n\u003cli\u003eMaster interactive development using the Jupyter platform\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eRun and build Docker containers from scratch and from publicly available open-source images\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eWrite infrastructure as code using the docker-compose tool and its docker-compose.yml file type\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eDeploy a multi-service data science application across a cloud-based system\u003cbr\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cdiv\u003eData scientists, machine learning engineers, artificial intelligence researchers, Kagglers, and software developers\u003c\/div\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003c\/div\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Apress\u003c\/p\u003e \u003cp\u003ePublication Date: 2017-08-25\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003eISBN-13: 9781484230114\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-1-4842-3012-1\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 257\u003c\/p\u003e ","brand":"Apress","offers":[{"title":"Default Title","offer_id":47522195046540,"sku":"9781484230114","price":53.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781484230114.jpg?v=1776013380","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9781484230114","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}