Mlops With Red Hat Openshift PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Mlops With Red Hat Openshift PDF full book. Access full book title Mlops With Red Hat Openshift.

MLOps with Red Hat OpenShift

MLOps with Red Hat OpenShift
Author: Ross Brigoli
Publisher: Packt Publishing Ltd
Total Pages: 238
Release: 2024-01-31
Genre: Computers
ISBN: 1805125850
GET BOOK

Download MLOps with Red Hat OpenShift Book in PDF, ePub and Kindle

Build and manage MLOps pipelines with this practical guide to using Red Hat OpenShift Data Science, unleashing the power of machine learning workflows Key Features Grasp MLOps and machine learning project lifecycle through concept introductions Get hands on with provisioning and configuring Red Hat OpenShift Data Science Explore model training, deployment, and MLOps pipeline building with step-by-step instructions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMLOps 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. With 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. As 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. Armed with this comprehensive knowledge, you’ll be able to implement MLOps workflows on the OpenShift platform proficiently.What you will learn Build a solid foundation in key MLOps concepts and best practices Explore MLOps workflows, covering model development and training Implement complete MLOps workflows on the Red Hat OpenShift platform Build MLOps pipelines for automating model training and deployments Discover model serving approaches using Seldon and Intel OpenVino Get to grips with operating data science and machine learning workloads in OpenShift Who this book is for This 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.

Mastering MLOps Architecture: From Code to Deployment

Mastering MLOps Architecture: From Code to Deployment
Author: Raman Jhajj
Publisher: BPB Publications
Total Pages: 284
Release: 2023-12-12
Genre: Computers
ISBN: 9355519494
GET BOOK

Download Mastering MLOps Architecture: From Code to Deployment Book in PDF, ePub and Kindle

Harness the power of MLOps for managing real time machine learning project cycle KEY FEATURES ● Comprehensive coverage of MLOps concepts, architecture, tools and techniques. ● Practical focus on building end-to-end ML Systems for Continual Learning with MLOps. ● Actionable insights on CI/CD, monitoring, continual model training and automated retraining. DESCRIPTION MLOps, a combination of DevOps, data engineering, and machine learning, is crucial for delivering high-quality machine learning results due to the dynamic nature of machine learning data. This book delves into MLOps, covering its core concepts, components, and architecture, demonstrating how MLOps fosters robust and continuously improving machine learning systems. By covering the end-to-end machine learning pipeline from data to deployment, the book helps readers implement MLOps workflows. It discusses techniques like feature engineering, model development, A/B testing, and canary deployments. The book equips readers with knowledge of MLOps tools and infrastructure for tasks like model tracking, model governance, metadata management, and pipeline orchestration. Monitoring and maintenance processes to detect model degradation are covered in depth. Readers can gain skills to build efficient CI/CD pipelines, deploy models faster, and make their ML systems more reliable, robust and production-ready. Overall, the book is an indispensable guide to MLOps and its applications for delivering business value through continuous machine learning and AI. WHAT YOU WILL LEARN ● Architect robust MLOps infrastructure with components like feature stores. ● Leverage MLOps tools like model registries, metadata stores, pipelines. ● Build CI/CD workflows to deploy models faster and continually. ● Monitor and maintain models in production to detect degradation. ● Create automated workflows for retraining and updating models in production. WHO THIS BOOK IS FOR Machine learning specialists, data scientists, DevOps professionals, software development teams, and all those who want to adopt the DevOps approach in their agile machine learning experiments and applications. Prior knowledge of machine learning and Python programming is desired. TABLE OF CONTENTS 1. Getting Started with MLOps 2. MLOps Architecture and Components 3. MLOps Infrastructure and Tools 4. What are Machine Learning Systems? 5. Data Preparation and Model Development 6. Model Deployment and Serving 7. Continuous Delivery of Machine Learning Models 8. Continual Learning 9. Continuous Monitoring, Logging, and Maintenance

DevOps with OpenShift

DevOps with OpenShift
Author: Stefano Picozzi
Publisher: "O'Reilly Media, Inc."
Total Pages: 148
Release: 2017-07-10
Genre: Computers
ISBN: 1491976616
GET BOOK

Download DevOps with OpenShift Book in PDF, ePub and Kindle

For many organizations, a big part of DevOps’ appeal is software automation using infrastructure-as-code techniques. This book presents developers, architects, and infra-ops engineers with a more practical option. You’ll learn how a container-centric approach from OpenShift, Red Hat’s cloud-based PaaS, can help your team deliver quality software through a self-service view of IT infrastructure. Three OpenShift experts at Red Hat explain how to configure Docker application containers and the Kubernetes cluster manager with OpenShift’s developer- and operational-centric tools. Discover how this infrastructure-agnostic container management platform can help companies navigate the murky area where infrastructure-as-code ends and application automation begins. Get an application-centric view of automation—and understand why it’s important Learn patterns and practical examples for managing continuous deployments such as rolling, A/B, blue-green, and canary Implement continuous integration pipelines with OpenShift’s Jenkins capability Explore mechanisms for separating and managing configuration from static runtime software Learn how to use and customize OpenShift’s source-to-image capability Delve into management and operational considerations when working with OpenShift-based application workloads Install a self-contained local version of the OpenShift environment on your computer

OpenShift for Developers

OpenShift for Developers
Author: Grant Shipley
Publisher: "O'Reilly Media, Inc."
Total Pages: 101
Release: 2016-08-04
Genre: Computers
ISBN: 1491961414
GET BOOK

Download OpenShift for Developers Book in PDF, ePub and Kindle

Keen to build web applications for the cloud? Get a quick hands-on introduction to OpenShift, the open source Platform as a Service (PaaS) offering from Red Hat. With this practical guide, you’ll learn the steps necessary to build, deploy, and host a complete real-world application on OpenShift without having to slog through long, detailed explanations of the technologies involved. OpenShift enables you to use Docker application containers and the Kubernetes cluster manager to automate the way you create, ship, and run applications. Through the course of the book, you’ll learn how to use OpenShift and the Wildfly application server to build and then immediately deploy a Java application online. Learn about OpenShift’s core technology, including Docker-based containers and Kubernetes Use a virtual machine with OpenShift installed and configured on your local environment Create and deploy your first application on the OpenShift platform Add language runtime dependencies and connect to a database Trigger an automatic rebuild and redeployment when you push changes to the repository Get a working environment up in minutes with application templates Use commands to check and debug your application Create and build Docker-based images for your application

Deploying to OpenShift

Deploying to OpenShift
Author: Graham Dumpleton
Publisher: "O'Reilly Media, Inc."
Total Pages: 162
Release: 2018-05-02
Genre: Computers
ISBN: 1491957123
GET BOOK

Download Deploying to OpenShift Book in PDF, ePub and Kindle

Get an in-depth tour of OpenShift, the container-based software deployment and management platform from Red Hat that provides a secure multi-tenant environment for the enterprise. This practical guide describes in detail how OpenShift, building on Kubernetes, enables you to automate the way you create, ship, and run applications in a containerized environment. Author Graham Dumpleton provides the knowledge you need to make the best use of the OpenShift container platform to deploy not only your cloud-native applications, but also more traditional stateful applications. Developers and administrators will learn how to run, access, and manage containers in OpenShift, including how to orchestrate them at scale. Build application container images from source and deploy them Implement and extend application image builders Use incremental and chained builds to accelerate build times Automate builds by using a webhook to link OpenShift to a Git repository Add configuration and secrets to the container as project resources Make an application visible outside the OpenShift cluster Manage persistent storage inside an OpenShift container Monitor application health and manage the application lifecycle This book is a perfect follow-up to OpenShift for Developers: A Guide for Impatient Beginners (O’Reilly).

Machine Learning on Kubernetes

Machine Learning on Kubernetes
Author: Faisal Masood
Publisher: Packt Publishing Ltd
Total Pages: 385
Release: 2022-06-24
Genre: Computers
ISBN: 1803231653
GET BOOK

Download Machine Learning on Kubernetes Book in PDF, ePub and Kindle

Build a Kubernetes-based self-serving, agile data science and machine learning ecosystem for your organization using reliable and secure open source technologies Key Features Build a complete machine learning platform on Kubernetes Improve the agility and velocity of your team by adopting the self-service capabilities of the platform Reduce time-to-market by automating data pipelines and model training and deployment Book Description MLOps is an emerging field that aims to bring repeatability, automation, and standardization of the software engineering domain to data science and machine learning engineering. By implementing MLOps with Kubernetes, data scientists, IT professionals, and data engineers can collaborate and build machine learning solutions that deliver business value for their organization. You'll begin by understanding the different components of a machine learning project. Then, you'll design and build a practical end-to-end machine learning project using open source software. As you progress, you'll understand the basics of MLOps and the value it can bring to machine learning projects. You will also gain experience in building, configuring, and using an open source, containerized machine learning platform. In later chapters, you will prepare data, build and deploy machine learning models, and automate workflow tasks using the same platform. Finally, the exercises in this book will help you get hands-on experience in Kubernetes and open source tools, such as JupyterHub, MLflow, and Airflow. By the end of this book, you'll have learned how to effectively build, train, and deploy a machine learning model using the machine learning platform you built. What you will learn Understand the different stages of a machine learning project Use open source software to build a machine learning platform on Kubernetes Implement a complete ML project using the machine learning platform presented in this book Improve on your organization's collaborative journey toward machine learning Discover how to use the platform as a data engineer, ML engineer, or data scientist Find out how to apply machine learning to solve real business problems Who this book is for This book is for data scientists, data engineers, IT platform owners, AI product owners, and data architects who want to build their own platform for ML development. Although this book starts with the basics, a solid understanding of Python and Kubernetes, along with knowledge of the basic concepts of data science and data engineering will help you grasp the topics covered in this book in a better way.

Red Hat OpenShift on IBM Z Installation Guide

Red Hat OpenShift on IBM Z Installation Guide
Author: Subhajit Maitra
Publisher: IBM Redbooks
Total Pages: 110
Release: 2020-10-16
Genre: Computers
ISBN: 0738459054
GET BOOK

Download Red Hat OpenShift on IBM Z Installation Guide Book in PDF, ePub and Kindle

This IBM® Redpaper publication provides all the necessary steps to successfully install Red Hat OpenShift 4.4 on IBM Z® or LinuxONE servers. It also provides an introduction to OpenShift nodes, Red Hat Enterprise Linux CoreOS, and Ansible. The steps that are described in this paper are taken from the official pages of the Red Hat website. This IBM Redpaper publication was written for IT architects, IT specialists, and others who are interested in installing Red Hat OpenShift on IBM Z.

DevOps Culture and Practice with OpenShift

DevOps Culture and Practice with OpenShift
Author: Tim Beattie
Publisher: Packt Publishing Ltd
Total Pages: 813
Release: 2021-08-23
Genre: Computers
ISBN: 180020650X
GET BOOK

Download DevOps Culture and Practice with OpenShift Book in PDF, ePub and Kindle

A practical guide to making the best use of the OpenShift container platform based on the real-life experiences, practices, and culture within Red Hat Open Innovation Labs Key FeaturesLearn how modern software companies deliver business outcomes that matter by focusing on DevOps culture and practicesAdapt Open Innovation Labs culture and foundational practices from the Open Practice LibraryImplement a metrics-driven approach to application, platform, and product, understanding what to measure and how to learn and pivotBook Description DevOps Culture and Practice with OpenShift features many different real-world practices - some people-related, some process-related, some technology-related - to facilitate successful DevOps, and in turn OpenShift, adoption within your organization. It introduces many DevOps concepts and tools to connect culture and practice through a continuous loop of discovery, pivots, and delivery underpinned by a foundation of collaboration and software engineering. Containers and container-centric application lifecycle management are now an industry standard, and OpenShift has a leading position in a flourishing market of enterprise Kubernetes-based product offerings. DevOps Culture and Practice with OpenShift provides a roadmap for building empowered product teams within your organization. This guide brings together lean, agile, design thinking, DevOps, culture, facilitation, and hands-on technical enablement all in one book. Through a combination of real-world stories, a practical case study, facilitation guides, and technical implementation details, DevOps Culture and Practice with OpenShift provides tools and techniques to build a DevOps culture within your organization on Red Hat's OpenShift Container Platform. What you will learnImplement successful DevOps practices and in turn OpenShift within your organizationDeal with segregation of duties in a continuous delivery worldUnderstand automation and its significance through an application-centric viewManage continuous deployment strategies, such as A/B, rolling, canary, and blue-greenLeverage OpenShift’s Jenkins capability to execute continuous integration pipelinesManage and separate configuration from static runtime softwareMaster communication and collaboration enabling delivery of superior software products at scale through continuous discovery and continuous deliveryWho this book is for This book is for anyone with an interest in DevOps practices with OpenShift or other Kubernetes platforms. This DevOps book gives software architects, developers, and infra-ops engineers a practical understanding of OpenShift, how to use it efficiently for the effective deployment of application architectures, and how to collaborate with users and stakeholders to deliver business-impacting outcomes.

OpenShift in Action

OpenShift in Action
Author: Jamie Duncan
Publisher: Pearson Professional
Total Pages: 292
Release: 2018
Genre: Computers
ISBN: 9781617294839
GET BOOK

Download OpenShift in Action Book in PDF, ePub and Kindle

Summary OpenShift in Action is a full reference to Red Hat OpenShift that breaks down this robust container platform so you can use it day-to-day. Combining Docker and Kubernetes, OpenShift is a powerful platform for cluster management, scaling, and upgrading your enterprise apps. It doesn't matter why you use OpenShift--by the end of this book you'll be able to handle every aspect of it, inside and out! Foreword by Jim Whitehurst, Red Hat. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Containers let you package everything into one neat place, and with Red Hat OpenShift you can build, deploy, and run those packages all in one place! Combining Docker and Kubernetes, OpenShift is a powerful platform for cluster management, scaling, and upgrading your enterprise apps. About the Book OpenShift in Action is a full reference to Red Hat OpenShift that breaks down this robust container platform so you can use it day-to-day. Starting with how to deploy and run your first application, you'll go deep into OpenShift. You'll discover crystal-clear explanations of namespaces, cgroups, and SELinux, learn to prepare a cluster, and even tackle advanced details like software-defined networks and security, with real-world examples you can take to your own work. It doesn't matter why you use OpenShift--by the end of this book you'll be able to handle every aspect of it, inside and out! What's Inside Written by lead OpenShift architects Rock-solid fundamentals of Docker and Kubernetes Keep mission-critical applications up and running Manage persistent storage About the Reader For DevOps engineers and administrators working in a Linux-based distributed environment. About the Authors Jamie Duncan is a cloud solutions architect for Red Hat, focusing on large-scale OpenShift deployments. John Osborne is a principal OpenShift architect for Red Hat. Table of Contents PART 1 - FUNDAMENTALS Getting to know OpenShift Getting started Containers are Linux PART 2 - CLOUD-NATIVE APPLICATIONS Working with services Autoscaling with metrics Continuous integration and continuous deployment PART 3 - STATEFUL APPLICATIONS Creating and managing persistent storage Stateful applications PART 4 - OPERATIONS AND SECURITY Authentication and resource access Networking Security

Machine Learning Theory and Applications

Machine Learning Theory and Applications
Author: Xavier Vasques
Publisher: John Wiley & Sons
Total Pages: 516
Release: 2024-03-06
Genre: Computers
ISBN: 1394220618
GET BOOK

Download Machine Learning Theory and Applications Book in PDF, ePub and Kindle

Enables readers to understand mathematical concepts behind data engineering and machine learning algorithms and apply them using open-source Python libraries Machine Learning Theory and Applications delves into the realm of machine learning and deep learning, exploring their practical applications by comprehending mathematical concepts and implementing them in real-world scenarios using Python and renowned open-source libraries. This comprehensive guide covers a wide range of topics, including data preparation, feature engineering techniques, commonly utilized machine learning algorithms like support vector machines and neural networks, as well as generative AI and foundation models. To facilitate the creation of machine learning pipelines, a dedicated open-source framework named hephAIstos has been developed exclusively for this book. Moreover, the text explores the fascinating domain of quantum machine learning and offers insights on executing machine learning applications across diverse hardware technologies such as CPUs, GPUs, and QPUs. Finally, the book explains how to deploy trained models through containerized applications using Kubernetes and OpenShift, as well as their integration through machine learning operations (MLOps). Additional topics covered in Machine Learning Theory and Applications include: Current use cases of AI, including making predictions, recognizing images and speech, performing medical diagnoses, creating intelligent supply chains, natural language processing, and much more Classical and quantum machine learning algorithms such as quantum-enhanced Support Vector Machines (QSVMs), QSVM multiclass classification, quantum neural networks, and quantum generative adversarial networks (qGANs) Different ways to manipulate data, such as handling missing data, analyzing categorical data, or processing time-related data Feature rescaling, extraction, and selection, and how to put your trained models to life and production through containerized applications Machine Learning Theory and Applications is an essential resource for data scientists, engineers, and IT specialists and architects, as well as students in computer science, mathematics, and bioinformatics. The reader is expected to understand basic Python programming and libraries such as NumPy or Pandas and basic mathematical concepts, especially linear algebra.