Operationalizing Machine Learning Pipelines: Building Reusable and Reproducible

Description: Operationalizing Machine Learning Pipelines by Vishwajyoti Pandey Shaleen Bengani This book provides a comprehensive guide to implementing MLOps using open-source tools on Google Cloud Platform. It covers the entire machine learning lifecycle, including training, deployment, monitoring, and automation. Aimed at ML specialists, data scientists, and engineers looking to enhance their MLOps knowledge. FORMAT Paperback CONDITION Brand New Publisher Description Implementing ML pipelines using MLOpsKey FeaturesIn-depth knowledge of MLOps, including recommendations for tools and processes.Includes only open-source cloud-agnostic tools for demonstrating MLOps.Covers end-to-end examples of implementing the whole process on Google Cloud Platform.DescriptionThis book will provide you with an in-depth understanding of MLOps and how you can use it inside an enterprise. Each tool discussed in this book has been thoroughly examined, providing examples of how to install and use them, as well as sample data.This book will teach you about every stage of the machine learning lifecycle and how to implement them within an organisation using a machine learning framework. With GitOps, youll learn how to automate operations and create reusable components such as feature stores for use in various contexts. You will learn to create a server-less training and deployment platform that scales automatically based on demand. You will learn about Polyaxon for machine learning model training, and KFServing, for model deployment. Additionally, you will understand how you should monitor machine learning models in production and what factors can degrade the models performance.You can apply the knowledge gained from this book to adopt MLOps in your organisation and tailor the requirements to your specific project. As you keep an eye on the models performance, youll be able to train and deploy it more quickly and with greater confidence.What you will learnQuick grasp of the entire machine learning lifecycle and tricks to manage all components.Learn to train and validate machine learning models for scalability.Get to know the pros of cloud computing for scaling ML operations.Covers aspects of ML operations, such as reproducibility and scalability, in detail.Get to know how to monitor machine learning models in production.Learn and practice automating the ML training and deployment processes.Who this book is forThis book is intended for machine learning specialists, data scientists, and data engineers who wish to improve and increase their MLOps knowledge to streamline machine learning initiatives. Readers with a working knowledge of the machine learning lifecycle would be advantageous.Table of Contents1. DS/ML Projects Initial Setup2. ML Projects Lifecycle3. ML Architecture Framework and Components4. Data Exploration and Quantifying Business Problem5. Training & Testing ML model6. ML model performance measurement7. CRUD operations with different JavaScript frameworks8. Feature Store9. Building ML PipelineRead more Details ISBN9355510233 Author Vishwajyoti Pandey Shaleen Bengani Pages 162 Year 2022 ISBN-10 9355510233 ISBN-13 9789355510235 Publication Date 2022-03-21 UK Release Date 2022-03-21 Format Paperback Imprint BPB Publications Place of Publication New Delhi Country of Publication India Subtitle Building Reusable and Reproducible Machine Learning Pipelines Using MLOps Publisher BPB Publications Audience General We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:134789249;

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