{"product_id":"mlops-with-red-hat-openshift-a-cloud-native-approach-to-machine-learning-operations-paperback","title":"MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eRoss Brigoli\u003c\/b\u003e (Author), \u003cb\u003eFaisal Masood\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eBuild and manage MLOps pipelines with this practical guide to using Red Hat OpenShift Data Science, unleashing the power of machine learning workflows\u003c\/strong\u003e\u003c\/p\u003eKey Features\u003cul\u003e\n\u003cli\u003eGrasp MLOps and machine learning project lifecycle through concept introductions\u003c\/li\u003e\n\u003cli\u003eGet hands on with provisioning and configuring Red Hat OpenShift Data Science\u003c\/li\u003e\n\u003cli\u003eExplore model training, deployment, and MLOps pipeline building with step-by-step instructions\u003c\/li\u003e\n\u003cli\u003ePurchase of the print or Kindle book includes a free PDF eBook\u003c\/li\u003e\n\u003c\/ul\u003eBook Description\u003cp\u003eMLOps with OpenShift offers practical insights for implementing MLOps workflows on the dynamic OpenShift platform. As organizations worldwide seek to harness the power of machine learning operations, this book lays the foundation for your MLOps success. Starting with an exploration of key MLOps concepts, including data preparation, model training, and deployment, you'll prepare to unleash OpenShift capabilities, kicking off with a primer on containers, pods, operators, and more.\u003c\/p\u003e\u003cp\u003eWith the groundwork in place, you'll be guided to MLOps workflows, uncovering the applications of popular machine learning frameworks for training and testing models on the platform.\u003c\/p\u003e\u003cp\u003eAs you advance through the chapters, you'll focus on the open-source data science and machine learning platform, Red Hat OpenShift Data Science, and its partner components, such as Pachyderm and Intel OpenVino, to understand their role in building and managing data pipelines, as well as deploying and monitoring machine learning models.\u003c\/p\u003e\u003cp\u003eArmed with this comprehensive knowledge, you'll be able to implement MLOps workflows on the OpenShift platform proficiently.\u003c\/p\u003eWhat you will learn\u003cul\u003e\n\u003cli\u003eBuild a solid foundation in key MLOps concepts and best practices\u003c\/li\u003e\n\u003cli\u003eExplore MLOps workflows, covering model development and training\u003c\/li\u003e\n\u003cli\u003eImplement complete MLOps workflows on the Red Hat OpenShift platform\u003c\/li\u003e\n\u003cli\u003eBuild MLOps pipelines for automating model training and deployments\u003c\/li\u003e\n\u003cli\u003eDiscover model serving approaches using Seldon and Intel OpenVino\u003c\/li\u003e\n\u003cli\u003eGet to grips with operating data science and machine learning workloads in OpenShift\u003c\/li\u003e\n\u003c\/ul\u003eWho this book is for\u003cp\u003eThis book is for MLOps and DevOps engineers, data architects, and data scientists interested in learning the OpenShift platform. Particularly, developers who want to learn MLOps and its components will find this book useful. Whether you're a machine learning engineer or software developer, this book serves as an essential guide to building scalable and efficient machine learning workflows on the OpenShift platform.\u003c\/p\u003eTable of Contents\u003col\u003e\n\u003cli\u003eIntroduction to MLOps and OpenShift\u003c\/li\u003e\n\u003cli\u003eProvisioning an MLOps platform in the Cloud\u003c\/li\u003e\n\u003cli\u003eBuilding Machine Learning Models\u003c\/li\u003e\n\u003cli\u003eEmbedding ML Models into the Applications\u003c\/li\u003e\n\u003cli\u003eDeploying ML Models as a Service\u003c\/li\u003e\n\u003cli\u003eOperating ML workloads\u003c\/li\u003e\n\u003cli\u003eBuilding a face detector using the Red Hat ML Platform\u003c\/li\u003e\n\u003c\/ol\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 238\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.5 x 9.25 x 7.5 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e January 31, 2024\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":43372554748039,"sku":"9781805120230","price":67.66,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0601\/2623\/2711\/files\/9fRggEvez19781805120230.webp?v=1761403815","url":"https:\/\/booksby.splitshops.com\/products\/mlops-with-red-hat-openshift-a-cloud-native-approach-to-machine-learning-operations-paperback","provider":"Books by splitShops","version":"1.0","type":"link"}