Description: Azure Machine Learning Engineering by Sina Fakhraee, Balamurugan Balakreshnan, Megan Masanz Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Data scientists working with Azure will be able to put their knowledge to work with this practical guide to Azure Machine Learning focused on leveraging the SDK V2 and CLI V2. With detailed steps and explanations, youll learn how to build and productionize end-to-end machine learning solutions using Azure ML. Publisher Description Fully build and productionize end-to-end machine learning solutions using Azure Machine Learning ServiceKey FeaturesAutomate complete machine learning solutions using Microsoft AzureUnderstand how to productionize machine learning modelsGet to grips with monitoring, MLOps, deep learning, distributed training, and reinforcement learningBook DescriptionData scientists working on productionizing machine learning (ML) workloads face a breadth of challenges at every step owing to the countless factors involved in getting ML models deployed and running. This book offers solutions to common issues, detailed explanations of essential concepts, and step-by-step instructions to productionize ML workloads using the Azure Machine Learning service. Youll see how data scientists and ML engineers working with Microsoft Azure can train and deploy ML models at scale by putting their knowledge to work with this practical guide.Throughout the book, youll learn how to train, register, and productionize ML models by making use of the power of the Azure Machine Learning service. Youll get to grips with scoring models in real time and batch, explaining models to earn business trust, mitigating model bias, and developing solutions using an MLOps framework.By the end of this Azure Machine Learning book, youll be ready to build and deploy end-to-end ML solutions into a production system using the Azure Machine Learning service for real-time scenarios.What you will learnTrain ML models in the Azure Machine Learning serviceBuild end-to-end ML pipelinesHost ML models on real-time scoring endpointsMitigate bias in ML modelsGet the hang of using an MLOps framework to productionize modelsSimplify ML model explainability using the Azure Machine Learning service and Azure InterpretWho this book is forMachine learning engineers and data scientists who want to move to ML engineering roles will find this AMLS book useful. Familiarity with the Azure ecosystem will assist with understanding the concepts covered. Author Biography Sina Fakhraee, Ph.D., is currently working at Microsoft as an enterprise data scientist and senior cloud solution architect. He has helped customers to successfully migrate to Azure by providing best practices around data and AI architectural design and by helping them implement AI/ML solutions on Azure. Prior to working at Microsoft, Sina worked at Ford Motor Company as a product owner for Fords AI/ML platform. Sina holds a Ph.D. degree in computer science and engineering from Wayne State University and prior to joining the industry, he taught various undergrad and grad computer science courses part time.Balamurugan Balakreshnan is a principal cloud solution architect at Microsoft Data/AI Architect and Data Science. He has provided leadership on digital transformations with AI and cloud-based digital solutions. He has also provided leadership in terms of ML, the IoT, big data, and advanced analytical solutions.Megan Masanz is a principal cloud solution architect at Microsoft focused on data, AI, and data science, passionately enabling organizations to address business challenges through the establishment of strategies and road maps for the planning, design, and deployment of Azure Cloud-based solutions. Megan is adept at paving the path to data science via computer science given her masters in computer science with a focus on data science. Details ISBN 1803239301 ISBN-13 9781803239309 Title Azure Machine Learning Engineering Author Sina Fakhraee, Balamurugan Balakreshnan, Megan Masanz Format Paperback Year 2023 Pages 362 Publisher Packt Publishing Limited GE_Item_ID:141640207; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. 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Price: 54.32 USD
Location: Fairfield, Ohio
End Time: 2024-09-14T03:11:57.000Z
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
ISBN-13: 9781803239309
Book Title: Azure Machine Learning Engineering
Publisher: Packt Publishing, The Limited
Subject: Data Modeling & Design, Image Processing, General, Computer Vision & Pattern Recognition
Publication Year: 2023
Number of Pages: 362 Pages
Language: English
Publication Name: Azure Machine Learning Engineering : Deploy, Fine-Tune, and Optimize ML Models Using Microsoft Azure
Type: Textbook
Subject Area: Computers, Science
Author: Balamurugan Balakreshnan, Sina Fakhraee, Megan Masanz
Format: Trade Paperback