Mastering Azure Machine Learning
DOWNLOAD eBooks
Download Mastering Azure Machine Learning PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Mastering Azure Machine Learning book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Mastering Azure Machine Learning
DOWNLOAD eBooks
Author : Christoph Korner
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-05-10
Mastering Azure Machine Learning written by Christoph Korner and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-10 with Computers categories.
Supercharge and automate your deployments to Azure Machine Learning clusters and Azure Kubernetes Service using Azure Machine Learning services Key Features Implement end-to-end machine learning pipelines on Azure Train deep learning models using Azure compute infrastructure Deploy machine learning models using MLOps Book Description Azure Machine Learning is a cloud service for accelerating and managing the machine learning (ML) project life cycle that ML professionals, data scientists, and engineers can use in their day-to-day workflows. This book covers the end-to-end ML process using Microsoft Azure Machine Learning, including data preparation, performing and logging ML training runs, designing training and deployment pipelines, and managing these pipelines via MLOps. The first section shows you how to set up an Azure Machine Learning workspace; ingest and version datasets; as well as preprocess, label, and enrich these datasets for training. In the next two sections, you'll discover how to enrich and train ML models for embedding, classification, and regression. You'll explore advanced NLP techniques, traditional ML models such as boosted trees, modern deep neural networks, recommendation systems, reinforcement learning, and complex distributed ML training techniques - all using Azure Machine Learning. The last section will teach you how to deploy the trained models as a batch pipeline or real-time scoring service using Docker, Azure Machine Learning clusters, Azure Kubernetes Services, and alternative deployment targets. By the end of this book, you'll be able to combine all the steps you've learned by building an MLOps pipeline. What you will learn Understand the end-to-end ML pipeline Get to grips with the Azure Machine Learning workspace Ingest, analyze, and preprocess datasets for ML using the Azure cloud Train traditional and modern ML techniques efficiently using Azure ML Deploy ML models for batch and real-time scoring Understand model interoperability with ONNX Deploy ML models to FPGAs and Azure IoT Edge Build an automated MLOps pipeline using Azure DevOps Who this book is for This book is for machine learning engineers, data scientists, and machine learning developers who want to use the Microsoft Azure cloud to manage their datasets and machine learning experiments and build an enterprise-grade ML architecture using MLOps. This book will also help anyone interested in machine learning to explore important steps of the ML process and use Azure Machine Learning to support them, along with building powerful ML cloud applications. A basic understanding of Python and knowledge of machine learning are recommended.
Mastering Azure Machine Learning
DOWNLOAD eBooks
Author : Christoph Körner
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-04-30
Mastering Azure Machine Learning written by Christoph Körner and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-30 with Computers categories.
Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and Kubernetes Key FeaturesMake sense of data on the cloud by implementing advanced analyticsTrain and optimize advanced deep learning models efficiently on Spark using Azure DatabricksDeploy machine learning models for batch and real-time scoring with Azure Kubernetes Service (AKS)Book Description The increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud. The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure Machine Learning and takes you through the process of data experimentation, data preparation, and feature engineering using Azure Machine Learning and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure Automated Machine Learning and HyperDrive, and perform distributed training on Azure. Then, you'll learn different deployment and monitoring techniques using Azure Kubernetes Services with Azure Machine Learning, along with the basics of MLOps—DevOps for ML to automate your ML process as CI/CD pipeline. By the end of this book, you'll have mastered Azure Machine Learning and be able to confidently design, build and operate scalable ML pipelines in Azure. What you will learnSetup your Azure Machine Learning workspace for data experimentation and visualizationPerform ETL, data preparation, and feature extraction using Azure best practicesImplement advanced feature extraction using NLP and word embeddingsTrain gradient boosted tree-ensembles, recommendation engines and deep neural networks on Azure Machine LearningUse hyperparameter tuning and Azure Automated Machine Learning to optimize your ML modelsEmploy distributed ML on GPU clusters using Horovod in Azure Machine LearningDeploy, operate and manage your ML models at scaleAutomated your end-to-end ML process as CI/CD pipelines for MLOpsWho this book is for This machine learning book is for data professionals, data analysts, data engineers, data scientists, or machine learning developers who want to master scalable cloud-based machine learning architectures in Azure. This book will help you use advanced Azure services to build intelligent machine learning applications. A basic understanding of Python and working knowledge of machine learning are mandatory.
Mastering Azure Machine Learning
DOWNLOAD eBooks
Author : Christoph Korner
language : en
Publisher:
Release Date : 2020
Mastering Azure Machine Learning written by Christoph Korner and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and Kubernetes Key Features Make sense of data on the cloud by implementing advanced analytics Train and optimize advanced deep learning models efficiently on Spark using Azure Databricks Deploy machine learning models for batch and real-time scoring with Azure Kubernetes Service (AKS) Book Description The increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud. The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure ML and takes you through the process of data experimentation, data preparation, and feature engineering using Azure ML and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure AutoML and HyperDrive, and perform distributed training on Azure ML. Then, you'll learn different deployment and monitoring techniques using Azure Kubernetes Services with Azure ML, along with the basics of MLOps-DevOps for ML to automate your ML process as CI/CD pipeline. By the end of this book, you'll have mastered Azure ML and be able to confidently design, build and operate scalable ML pipelines in Azure. What you will learn Setup your Azure ML workspace for data experimentation and visualization Perform ETL, data preparation, and feature extraction using Azure best practices Implement advanced feature extraction using NLP and word embeddings Train gradient boosted tree-ensembles, recommendation engines and deep neural networks on Azure ML Use hyperparameter tuning and AutoML to optimize your ML models Employ distributed ML on GPU clusters using Horovod in Azure ML Deploy, operate and manage your ML models at scale Automated your end-to-end ML process as CI/CD pipelines for MLOps Who this book is for This machine learning book is for data professionals, data analysts, data enginee...
Mastering Azure Analytics
DOWNLOAD eBooks
Author : Zoiner Tejada
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-04-06
Mastering Azure Analytics written by Zoiner Tejada and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-06 with Computers categories.
Microsoft Azure has over 20 platform-as-a-service (PaaS) offerings that can act in support of a big data analytics solution. So which one is right for your project? This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution. You’ll not only be able to determine which service best fits the job, but also learn how to implement a complete solution that scales, provides human fault tolerance, and supports future needs. Understand the fundamental patterns of the data lake and lambda architecture Recognize the canonical steps in the analytics data pipeline and learn how to use Azure Data Factory to orchestrate them Implement data lakes and lambda architectures, using Azure Data Lake Store, Data Lake Analytics, HDInsight (including Spark), Stream Analytics, SQL Data Warehouse, and Event Hubs Understand where Azure Machine Learning fits into your analytics pipeline Gain experience using these services on real-world data that has real-world problems, with scenarios ranging from aviation to Internet of Things (IoT)
Mastering Microsoft Azure For Ai A Beginner S Guide
DOWNLOAD eBooks
Author : M.B. Chatfield
language : en
Publisher:
Release Date :
Mastering Microsoft Azure For Ai A Beginner S Guide written by M.B. Chatfield and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Mastering Microsoft Azure for AI: A Beginner's Guide is the definitive guide for anyone who wants to learn how to build and deploy artificial intelligence (AI) solutions on Microsoft Azure. This comprehensive book covers everything you need to know, from the basics of AI to the latest Azure AI services and technologies. Learn the fundamentals of AI Explore Azure AI services and technologies Build and deploy your own AI solutions Whether you're a beginner or an experienced developer, Mastering Microsoft Azure for AI: A Beginner's Guide is the perfect resource for learning how to build and deploy AI solutions on Microsoft Azure.
Mastering Azure Synapse Analytics
DOWNLOAD eBooks
Author :
language : en
Publisher: BPB Publications
Release Date : 2023-04-15
Mastering Azure Synapse Analytics written by and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-15 with Computers categories.
A practical guide that will help you transform your data into actionable insights with Azure Synapse Analytics KEY FEATURES ● Explore the different features in the Azure Synapse Analytics workspace. ● Learn how to integrate Power BI and Data Governance capabilities with Azure Synapse Analytics. ● Accelerate your analytics journey with the no-code/low-code capabilities of Azure Synapse. DESCRIPTION Cloud analytics is a crucial aspect of any digital transformation initiative, and the capabilities of the Azure Synapse analytics platform can simplify and streamline this process. By mastering Azure Synapse Analytics, analytics developers across organizations can boost their productivity by utilizing low-code, no-code, and traditional code-based analytics frameworks. This book starts with a comprehensive introduction to Azure Synapse Analytics and its limitless cloud-scale analytics capabilities. You will then learn how to explore and work with data warehousing features in Azure Synapse. Moving on, the book will guide you on how to effectively use Synapse Spark for data engineering and data science. It will help you learn how to gain insights from your data through Observational analytics using Synapse Data Explorer. You will also discover the seamless data integration capabilities of Synapse Pipeline, and delve into the benefits of Synapse Analytics' low-code and no-code pipeline development features. Lastly the book will show you how to create network topology and implement industry-specific architecture patterns in Azure Synapse Analytics. By the end of the book, you will be able to process and analyze vast amounts of data in real-time to gain insights quickly and make informed decisions. WHAT YOU WILL LEARN ● Leverage Synapse Spark for machine learning tasks. ● Use Synapse Data Explorer for telemetry analysis. ● Take advantage of Synapse's common data model-based database templates. ● Query data using T-SQL, KQL, and Spark SQL within Synapse. ● Integrate Microsoft Purview with Synapse for enhanced data governance. WHO THIS BOOK IS FOR This book is designed for Cloud data engineers with prior experience in Azure cloud computing, as well as Chief Data Officers (CDOs) and Data professionals, who want to use this unified platform for data ingestion, data warehousing, and big data analytics. TABLE OF CONTENTS 1. Cloud Analytics Concept 2. Introduction to Azure Synapse Analytics 3. Modern Data Warehouse with the Synapse SQL Pool 4. Query as a Service- Synapse Serverless SQL 5. Synapse Spark Pool Capability 6. Synapse Spark and Data Science 7. Learning Synapse Data Explorer 8. Synapse Data Integration 9. Synapse Link for HTAP 10. Azure Synapse -Unified Analytics Service 11. Synapse Workspace Ecosystem Integration 12. Azure Synapse Network Topology 13. Industry Cloud Analytics
Demystifying Ai A Comprehensive Guide To Microsoft Certified Azure Ai Fundamentals
DOWNLOAD eBooks
Author : Mark Duncan
language : en
Publisher: LLZ Publishing
Release Date :
Demystifying Ai A Comprehensive Guide To Microsoft Certified Azure Ai Fundamentals written by Mark Duncan and has been published by LLZ Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on with Antiques & Collectibles categories.
"Unlocking Azure AI" is a comprehensive guide that provides readers with a deep dive into the world of artificial intelligence (AI) on the Microsoft Azure platform. This book serves as a roadmap for individuals looking to explore, understand, and leverage the full potential of Azure AI services to solve real-world problems and drive innovation. With the exponential growth of AI technologies and their increasing integration into various industries and applications, there is a growing demand for professionals who possess the knowledge and skills to develop, deploy, and manage AI solutions on cloud platforms like Azure. "Unlocking Azure AI" addresses this need by offering a structured and accessible approach to learning Azure AI concepts and services. The book begins by introducing readers to the fundamentals of AI, providing a foundational understanding of key concepts such as machine learning, natural language processing, computer vision, and conversational AI. Readers will learn how AI is transforming industries and reshaping the way businesses operate and interact with customers. As readers progress through the book, they will explore the rich ecosystem of Azure AI services offered by Microsoft, including Azure Cognitive Services, Azure Machine Learning, and Azure Bot Services. Each chapter delves into a specific aspect of Azure AI, covering topics such as: Understanding the capabilities and use cases of Azure Cognitive Services, including vision, speech, language, and decision services. Building and training machine learning models using Azure Machine Learning, from data preparation and model development to deployment and management. Developing intelligent chatbots and virtual agents using Azure Bot Services to automate customer support and enhance user experiences. The book provides practical guidance, hands-on examples, and real-world case studies to illustrate how Azure AI services can be applied to solve common business challenges across various industries. Readers will learn how to leverage Azure AI to enhance productivity, drive innovation, and gain competitive advantage in today's digital economy. In addition to technical content, "Unlocking Azure AI" also addresses ethical considerations and implications in AI development and deployment, helping readers understand the importance of responsible AI practices and ensuring fairness, transparency, and accountability in AI systems. Whether you're a developer, data scientist, IT professional, or business leader, "Unlocking Azure AI" is your go-to resource for mastering Azure AI and unlocking the full potential of artificial intelligence on the Microsoft Azure platform. With its comprehensive coverage, practical insights, and actionable advice, this book empowers readers to embark on their Azure AI journey with confidence and competence.
Automated Machine Learning With Microsoft Azure
DOWNLOAD eBooks
Author : Dennis Michael Sawyers
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-04-23
Automated Machine Learning With Microsoft Azure written by Dennis Michael Sawyers and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-23 with Computers categories.
A practical, step-by-step guide to using Microsoft's AutoML technology on the Azure Machine Learning service for developers and data scientists working with the Python programming language Key FeaturesCreate, deploy, productionalize, and scale automated machine learning solutions on Microsoft AzureImprove the accuracy of your ML models through automatic data featurization and model trainingIncrease productivity in your organization by using artificial intelligence to solve common problemsBook Description Automated Machine Learning with Microsoft Azure will teach you how to build high-performing, accurate machine learning models in record time. It will equip you with the knowledge and skills to easily harness the power of artificial intelligence and increase the productivity and profitability of your business. Guided user interfaces (GUIs) enable both novices and seasoned data scientists to easily train and deploy machine learning solutions to production. Using a careful, step-by-step approach, this book will teach you how to use Azure AutoML with a GUI as well as the AzureML Python software development kit (SDK). First, you'll learn how to prepare data, train models, and register them to your Azure Machine Learning workspace. You'll then discover how to take those models and use them to create both automated batch solutions using machine learning pipelines and real-time scoring solutions using Azure Kubernetes Service (AKS). Finally, you will be able to use AutoML on your own data to not only train regression, classification, and forecasting models but also use them to solve a wide variety of business problems. By the end of this Azure book, you'll be able to show your business partners exactly how your ML models are making predictions through automatically generated charts and graphs, earning their trust and respect. What you will learnUnderstand how to train classification, regression, and forecasting ML algorithms with Azure AutoMLPrepare data for Azure AutoML to ensure smooth model training and deploymentAdjust AutoML configuration settings to make your models as accurate as possibleDetermine when to use a batch-scoring solution versus a real-time scoring solutionProductionalize your AutoML and discover how to quickly deliver valueCreate real-time scoring solutions with AutoML and Azure Kubernetes ServiceTrain a large number of AutoML models at once using the AzureML Python SDKWho this book is for Data scientists, aspiring data scientists, machine learning engineers, or anyone interested in applying artificial intelligence or machine learning in their business will find this machine learning book useful. You need to have beginner-level knowledge of artificial intelligence and a technical background in computer science, statistics, or information technology before getting started. Familiarity with Python will help you implement the more advanced features found in the chapters, but even data analysts and SQL experts will be able to train ML models after finishing this book.
Hands On Machine Learning With Azure
DOWNLOAD eBooks
Author : Thomas K Abraham
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-10-31
Hands On Machine Learning With Azure written by Thomas K Abraham and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-31 with Computers categories.
Implement machine learning, cognitive services, and artificial intelligence solutions by leveraging Azure cloud technologies Key FeaturesLearn advanced concepts in Azure ML and the Cortana Intelligence Suite architectureExplore ML Server using SQL Server and HDInsight capabilitiesImplement various tools in Azure to build and deploy machine learning modelsBook Description Implementing Machine learning (ML) and Artificial Intelligence (AI) in the cloud had not been possible earlier due to the lack of processing power and storage. However, Azure has created ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML projects in the cloud in a cost-effective way. The book begins by covering the benefits of ML and AI in the cloud. You will then explore Microsoft’s Team Data Science Process to establish a repeatable process for successful AI development and implementation. You will also gain an understanding of AI technologies available in Azure and the Cognitive Services APIs to integrate them into bot applications. This book lets you explore prebuilt templates with Azure Machine Learning Studio and build a model using canned algorithms that can be deployed as web services. The book then takes you through a preconfigured series of virtual machines in Azure targeted at AI development scenarios. You will get to grips with the ML Server and its capabilities in SQL and HDInsight. In the concluding chapters, you’ll integrate patterns with other non-AI services in Azure. By the end of this book, you will be fully equipped to implement smart cognitive actions in your models. What you will learnDiscover the benefits of leveraging the cloud for ML and AIUse Cognitive Services APIs to build intelligent botsBuild a model using canned algorithms from Microsoft and deploy it as a web serviceDeploy virtual machines in AI development scenariosApply R, Python, SQL Server, and Spark in AzureBuild and deploy deep learning solutions with CNTK, MMLSpark, and TensorFlowImplement model retraining in IoT, Streaming, and Blockchain solutionsExplore best practices for integrating ML and AI functions with ADLA and logic appsWho this book is for If you are a data scientist or developer familiar with Azure ML and cognitive services and want to create smart models and make sense of data in the cloud, this book is for you. You’ll also find this book useful if you want to bring powerful machine learning services into your cloud applications. Some experience with data manipulation and processing, using languages like SQL, Python, and R, will aid in understanding the concepts covered in this book
Azure Machine Learning Engineering
DOWNLOAD eBooks
Author : Sina Fakhraee
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-01-20
Azure Machine Learning Engineering written by Sina Fakhraee and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Computers categories.
Fully build and productionize end-to-end machine learning solutions using Azure Machine Learning Service Key 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 Description Data 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. You'll 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, you'll learn how to train, register, and productionize ML models by making use of the power of the Azure Machine Learning service. You'll 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, you'll 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 for Machine 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.