Data Science Solutions on Azure: Tools and Techniques Using Databricks and MLOps

Description: Data Science Solutions on Azure by Julian Soh, Priyanshi Singh Understand and learn the skills needed to use modern tools in Microsoft Azure. This book discusses how to practically apply these tools in the industry, and help drive the transformation of organizations into a knowledge and data-driven entity. It provides an end-to-end understanding of data science life cycle and the techniques to efficiently productionize workloads. The book starts with an introduction to data science and discusses the statistical techniques data scientists should know. Youll then move on to machine learning in Azure where you will review the basics of data preparation and engineering, along with Azure ML service and automated machine learning. Youll also explore Azure Databricks and learn how to deploy, create and manage the same. In the final chapters youll go through machine learning operations in Azure followed by the practical implementation of artificial intelligence through machine learning. Data Science Solutions on Azure will reveal how the different Azure services work together using real life scenarios and how-to-build solutions in a single comprehensive cloud ecosystem. What Youll LearnUnderstand big data analytics with Spark in Azure Databricks Integrate with Azure services like Azure Machine Learning and Azure SynapsDeploy, publish and monitor your data science workloads with MLOps Review data abstraction, model management and versioning with GitHubWho This Book Is ForData Scientists looking to deploy end-to-end solutions on Azure with latest tools and techniques. FORMAT Paperback LANGUAGE English CONDITION Brand New Back Cover Understand and learn the skills needed to use modern tools in Microsoft Azure. This book discusses how to practically apply these tools in the industry, and help drive the transformation of organizations into a knowledge and data-driven entity. It provides an end-to-end understanding of data science life cycle and the techniques to efficiently productionize workloads. The book starts with an introduction to data science and discusses the statistical techniques data scientists should know. Youll then move on to machine learning in Azure where you will review the basics of data preparation and engineering, along with Azure ML service and automated machine learning. Youll also explore Azure Databricks and learn how to deploy, create and manage the same. In the final chapters youll go through machine learning operations in Azure followed by the practical implementation of artificial intelligence through machine learning. Data Science Solutions on Azure will reveal how the different Azure services work together using real life scenarios and how-to-build solutions in a single comprehensive cloud ecosystem. You will: Understand big data analytics with Spark in Azure Databricks Integrate with Azure services like Azure Machine Learning and Azure Synaps Deploy, publish and monitor your data science workloads with MLOps Review data abstraction, model management and versioning with GitHub Author Biography Julian Soh is a cloud solutions architect with Microsoft, focusing in the areas of artificial intelligence, cognitive services, and advanced analytics. Prior to his current role, Julian worked extensively in major public cloud initiatives, such as SaaS (Microsoft Office 365), IaaS/PaaS (Microsoft Azure), and hybrid private-public cloud implementations.Priyanshi Singh is a data scientist by training and a data enthusiast by nature specializing in machine learning techniques applied to predictive analytics, computer vision and natural language processing. She holds a masters degree in Data Science from New York University and is currently a Cloud Solution Architect at Microsoft helping the public sector to transform citizen services with Artificial Intelligence. She also leads a meetup community based out of New York to help educate public sector employees via hands on labs and discussions. Apart from her passion for learning new technologies and innovating with AI, she is a sports enthusiast, a great badminton player and enjoys playing Billiards. Find her on LinkedIn at Table of Contents Chapter 1: Data Science in the Modern Enterprise.- Chapter 2: Statistical Techniques and Concepts in Data Science.- Chapter 3: Data Preparation and Data Engineering Basics.- Chapter 4: Introduction to Azure Machine Learning.- Chapter 5: Hands on with Azure Machine Learning.- Chapter 6: Apache Spark, Big Data, and Azure Databricks.- Chapter 7: Hands-on with Azure Databricks.- Chapter 8: Machine Learning Operations. Feature Holistic coverage of Azure data science capabilities Covers Azure Cognitive Services API for AI developers Consists of Case Studies for each operation discussed Details ISBN1484264045 Author Priyanshi Singh Short Title Data Science Solutions on Azure Language English ISBN-10 1484264045 ISBN-13 9781484264041 Format Paperback DOI 10.1007/978-1-4842-6405-8 Pages 285 Year 2020 Publication Date 2020-12-19 UK Release Date 2020-12-19 Edition 1st Imprint APress Place of Publication Berkley Country of Publication United States AU Release Date 2020-12-19 NZ Release Date 2020-12-19 US Release Date 2020-12-19 Illustrations 186 Illustrations, black and white; XIII, 285 p. 186 illus. Publisher APress Edition Description 1st ed. Subtitle Tools and Techniques Using Databricks and MLOps DEWEY 004.6782 Audience Professional & Vocational Replaced by 9798868809132 We've got this At The Nile, if you're looking for it, we've got it. 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