Download or read book Exam Ref 70 774 Perform Cloud Data Science with Azure Machine Learning written by Ginger Grant and published by Microsoft Press. This book was released on 2018-03-01 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare for Microsoft Exam 70-774–and help demonstrate your real-world mastery of performing key data science activities with Azure Machine Learning services. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the MCSA level. Focus on the expertise measured by these objectives: Prepare data for analysis in Azure Machine Learning and export from Azure Machine Learning Develop machine learning models Operationalize and manage Azure Machine Learning Services Use other services for machine learning This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are familiar with Azure data services, machine learning concepts, and common data science processes About the Exam Exam 70-774 focuses on skills and knowledge needed to prepare data for analysis with Azure Machine Learning; find key variables describing your data’s behavior; develop models and identify optimal algorithms; train, validate, deploy, manage, and consume Azure Machine Learning Models; and leverage related services and APIs. About Microsoft Certification Passing this exam as well as Exam 70-773: Analyzing Big Data with Microsoft R earns your MCSA: Machine Learning certifi¿cation, demonstrating your expertise in operationalizing Microsoft Azure machine learning and Big Data with R Server and SQL R Services. See full details at: microsoft.com/learning

Download or read book Azure Data Scientist Associate Certification Guide written by Andreas Botsikas and published by Packt Publishing Ltd. This book was released on 2021-12-03 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop the skills you need to run machine learning workloads in Azure and pass the DP-100 exam with ease Key FeaturesCreate end-to-end machine learning training pipelines, with or without codeTrack experiment progress using the cloud-based MLflow-compatible process of Azure ML servicesOperationalize your machine learning models by creating batch and real-time endpointsBook Description The Azure Data Scientist Associate Certification Guide helps you acquire practical knowledge for machine learning experimentation on Azure. It covers everything you need to pass the DP-100 exam and become a certified Azure Data Scientist Associate. Starting with an introduction to data science, you'll learn the terminology that will be used throughout the book and then move on to the Azure Machine Learning (Azure ML) workspace. You'll discover the studio interface and manage various components, such as data stores and compute clusters. Next, the book focuses on no-code and low-code experimentation, and shows you how to use the Automated ML wizard to locate and deploy optimal models for your dataset. You'll also learn how to run end-to-end data science experiments using the designer provided in Azure ML Studio. You'll then explore the Azure ML Software Development Kit (SDK) for Python and advance to creating experiments and publishing models using code. The book also guides you in optimizing your model's hyperparameters using Hyperdrive before demonstrating how to use responsible AI tools to interpret and debug your models. Once you have a trained model, you'll learn to operationalize it for batch or real-time inferences and monitor it in production. By the end of this Azure certification study guide, you'll have gained the knowledge and the practical skills required to pass the DP-100 exam. What you will learnCreate a working environment for data science workloads on AzureRun data experiments using Azure Machine Learning servicesCreate training and inference pipelines using the designer or codeDiscover the best model for your dataset using Automated MLUse hyperparameter tuning to optimize trained modelsDeploy, use, and monitor models in productionInterpret the predictions of a trained modelWho this book is for This book is for developers who want to infuse their applications with AI capabilities and data scientists looking to scale their machine learning experiments in the Azure cloud. Basic knowledge of Python is needed to follow the code samples used in the book. Some experience in training machine learning models in Python using common frameworks like scikit-learn will help you understand the content more easily.

Download or read book Exam Ref Dp 100 Designing and Implementing a Data Science Solution on Azure written by Pierstefano Tucci and published by Microsoft Press. This book was released on 2021-03-30 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare for Microsoft Exam DP-100-and help demonstrate your real-world mastery of the various data science components of Microsoft Azure. Designed for IT professionals, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified Associate level. Focus on the expertise measured by these objectives: Set up an Azure Machine Learning workspace Run experiments and train models Optimize and manage models Deploy and consume models This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are a business user, IT professional, or student interested in cloud computing and technologies, including individuals planning to pursue more advanced Microsoft 365 certification About the Exam Exam DP-100 focuses on knowledge needed to apply scientific rigor and data exploration techniques to gain actionable insights and communicate results to stakeholders; use machine learning techniques to train, evaluate, and deploy models to build AI solutions that satisfy business objectives; use applications that involve natural language processing, speech, computer vision, and predictive analytics. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Azure Data Scientist Associate credential, demonstrating that you understand how to implement and run machine learning workloads on Microsoft Azure; in particular, using Azure Machine Learning Service. See full details at: www.microsoft.com/learn

Download or read book Exam Ref AI 900 Microsoft Azure AI Fundamentals written by Julian Sharp and published by Microsoft Press. This book was released on 2021-11-16 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare for Microsoft Exam AI-900 and help demonstrate your real-world knowledge of diverse machine learning (ML) and artificial intelligence (AI) workloads, and how they can be implemented with Azure AI. Designed for business stakeholders, new and existing IT professionals, consultants, and students, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure AI Fundamentals level. Focus on the expertise measured by these objectives: • Describe AI workloads and considerations • Describe fundamental principles of machine learning on Azure • Describe features of computer vision workloads on Azure • Describe features of Natural Language Processing (NLP) workloads on Azure • Describe features of conversational AI workloads on Azure This Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you are a business user, stakeholder, technical professional, or student who wants to become familiar with Azure AI; requires no data science or software engineering experience. About the Exam Exam AI-900 focuses on knowledge needed to identify features of common AI workloads and guiding principles for responsible AI; identify common ML types; describe core ML concepts; identify core tasks in creating an ML solution; describe capabilities of no-code ML with Azure Machine Learning Studio; identify common types of computer vision solutions; identify Azure tools and services for computer vision tasks; identify features of common NLP workload scenarios; identify Azure tools and services for NLP workloads; and identify common use cases and Azure services for conversational Al. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Azure AI Fundamentals certification, demonstrating your knowledge of common ML and AI workloads and how to implement them on Azure. With this certification, you can move on to earn more advanced role-based certifications, including Microsoft Certified: Azure AI Engineer Associate or Azure Data Scientist Associate. See full details at: microsoft.com/learn

Download or read book Mastering Azure Analytics written by Zoiner Tejada and published by "O'Reilly Media, Inc.". This book was released on 2017-04-06 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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)

Download or read book Ultimate Azure Data Scientist Associate DP 100 Certification Guide written by Rajib Kumar De and published by Orange Education Pvt Ltd. This book was released on 2024-06-26 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: TAGLINE Empower Your Data Science Journey: From Exploration to Certification in Azure Machine Learning KEY FEATURES ● Offers deep dives into key areas such as data preparation, model training, and deployment, ensuring you master each concept. ● Covers all exam objectives in detail, ensuring a thorough understanding of each topic required for the DP-100 certification. ● Includes hands-on labs and practical examples to help you apply theoretical knowledge to real-world scenarios, enhancing your learning experience. DESCRIPTION Ultimate Azure Data Scientist Associate (DP-100) Certification Guide is your essential resource for achieving the Microsoft Azure Data Scientist Associate certification. This guide covers all exam objectives, helping you design and prepare machine learning solutions, explore data, train models, and manage deployment and retraining processes. The book starts with the basics and advances through hands-on exercises and real-world projects, to help you gain practical experience with Azure's tools and services. The book features certification-oriented Q&A challenges that mirror the actual exam, with detailed explanations to help you thoroughly grasp each topic. Perfect for aspiring data scientists, IT professionals, and analysts, this comprehensive guide equips you with the expertise to excel in the DP-100 exam and advance your data science career. WHAT WILL YOU LEARN ● Design and prepare effective machine learning solutions in Microsoft Azure. ● Learn to develop complete machine learning training pipelines, with or without code. ● Explore data, train models, and validate ML pipelines efficiently. ● Deploy, manage, and optimize machine learning models in Azure. ● Utilize Azure's suite of data science tools and services, including Prompt Flow, Model Catalog, and AI Studio. ● Apply real-world data science techniques to business problems. ● Confidently tackle DP-100 certification exam questions and scenarios. WHO IS THIS BOOK FOR? This book is for aspiring Data Scientists, IT Professionals, Developers, Data Analysts, Students, and Business Professionals aiming to Master Azure Data Science. Prior knowledge of basic Data Science concepts and programming, particularly in Python, will be beneficial for making the most of this comprehensive guide. TABLE OF CONTENTS 1. Introduction to Data Science and Azure 2. Setting Up Your Azure Environment 3. Data Ingestion and Storage in Azure 4. Data Transformation and Cleaning 5. Introduction to Machine Learning 6. Azure Machine Learning Studio 7. Model Deployment and Monitoring 8. Embracing AI Revolution Azure 9. Responsible AI and Ethics 10. Big Data Analytics with Azure 11. Real-World Applications and Case Studies 12. Conclusion and Next Steps Index

Download or read book Exam Ref DP 900 Microsoft Azure Data Fundamentals written by Nicola Farquharson and published by Microsoft Press. This book was released on 2024-05-07 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare for Microsoft Exam DP-900 and demonstrate your real-world foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services. Designed for business users, functional consultants, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure Data Fundamentals level. Focus on the expertise measured by these objectives: Describe core data concepts within Microsoft Azure Describe how to work with both relational and non-relational data types on Azure Describe strategic application, data management, storage and processing in the Azure cloud environment Describe an analytics workload on Azure This Microsoft Exam Ref: Organizes its coverage by the Skills Measured list published for the exam Features strategic, what-if scenarios to challenge you Assumes you have foundational knowledge of core data concepts and their implementation with Microsoft Azure data services, and a general grasp of cloud concepts

Download or read book Hands On Machine Learning with Azure written by Thomas K Abraham and published by Packt Publishing Ltd. This book was released on 2018-10-31 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Mastering Azure Machine Learning written by Christoph Körner and published by Packt Publishing Ltd. This book was released on 2020-04-30 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Exam Ref DP 900 Microsoft Azure Data Fundamentals written by Daniel A. Seara and published by Microsoft Press. This book was released on 2021-03-12 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare for Microsoft Exam DP-900 Demonstrate your real-world foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services. Designed for business users, functional consultants, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure Data Fundamentals level. Focus on the expertise measured by these objectives: Describe core data concepts Describe how to work with relational data on Azure Describe how to work with non-relational data on Azure Describe an analytics workload on Azure This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you have foundational knowledge of core data concepts and their implementation with Microsoft Azure data services, and are beginning to work with data in the cloud About the Exam Exam DP-900 focuses on core knowledge for describing fundamental database concepts and skills for cloud environments; cloud data services within Azure; cloud data roles, tasks, and responsibilities; Azure relational and non-relational data offerings, provisioning, and deployment; querying Azure relational databases; working with Azure non-relational data stores; building modern Azure data analytics solutions; and exploring Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Azure Data Fundamentals certification, demonstrating your understanding of the core capabilities of Azure data services and their use with relational data, non-relational data, and analytics workloads. See full details at: www.microsoft.com/learn

Download or read book Predictive Analytics with Microsoft Azure Machine Learning 2nd Edition written by Valentine Fontama and published by Apress. This book was released on 2015-08-26 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models. The authors use task oriented descriptions and concrete end-to-end examples to ensure that the reader can immediately begin using this new service. The book describes all aspects of the service from data ingress to applying machine learning, evaluating the models, and deploying them as web services. Learn how you can quickly build and deploy sophisticated predictive models with the new Azure Machine Learning from Microsoft. What’s New in the Second Edition? Five new chapters have been added with practical detailed coverage of: Python Integration – a new feature announced February 2015 Data preparation and feature selection Data visualization with Power BI Recommendation engines Selling your models on Azure Marketplace

Download or read book Predictive Analytics with Microsoft Azure Machine Learning written by Valentine Fontama and published by Apress. This book was released on 2014-11-25 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter. The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft.

Download or read book Exam Ref DP 500 Designing and Implementing Enterprise Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI written by Daniil Maslyuk and published by Microsoft Press. This book was released on 2023-07-09 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare for Microsoft Exam DP-500 and demonstrate your real-world ability to design, create, and deploy enterprise-scale data analytics solutions. Designed for business intelligence developers, architects, data analysts, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure Enterprise Data Analyst Associate level. Focus on the expertise measured by these objectives: Implement and manage a data analytics environment Query and transform data Implement and manage data models Explore and visualize data This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are a business intelligence developer, architect, data engineer, data architect, data analyst, or another professional with Power BI and Azure experience. About the Exam Exam DP-500 focuses on knowledge needed to govern and administer data analytics environments; integrate analytics platforms into existing IT infrastructure; manage the analytics development lifecycle; query data with Azure Synapse Analytics; ingest and transform data with Power BI; design and build tabular models; optimize enterprise-scale data models; explore data with Azure Synapse Analytics; and visualize data with Power BI. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Azure Enterprise Data Analyst Associate certification, demonstrating your knowledge of designing, creating, and deploying enterprise-scale data analytics solutions. Responsibilities include performing advanced data analytics at scale, collecting enterprise-level requirements for data analytics solutions that include Azure and Microsoft Power BI, advising on data governance and configuration for Power BI administration, monitoring data usage, and optimizing solution performance. See full details at: microsoft.com/learn

Download or read book Automated Machine Learning with Microsoft Azure written by Dennis Michael Sawyers and published by Packt Publishing Ltd. This book was released on 2021-04-23 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Microsoft Certified Exam guide Azure AI Engineer Associate AI 102 written by Cybellium Ltd and published by Cybellium Ltd. This book was released on with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: Become the Azure AI Expert of Tomorrow! Are you ready to embark on a journey into the world of artificial intelligence and machine learning within the Microsoft Azure ecosystem? Look no further than the "Microsoft Certified Exam Guide - Azure AI Engineer Associate (AI-102)." This comprehensive book is your ultimate companion on the path to mastering Azure AI and acing the AI-102 exam. In today's era of data-driven decision-making, AI and machine learning are the driving forces behind innovation and transformation. Microsoft Azure provides a robust platform for developing AI solutions, and organizations worldwide are seeking AI experts who can leverage its capabilities. Whether you're an AI enthusiast, a data scientist, or an IT professional, this book equips you with the knowledge and skills needed to excel in Azure AI. Inside this book, you will discover: ✔ Comprehensive Coverage: A deep dive into all the essential AI concepts, tools, and best practices for designing, implementing, and maintaining AI solutions on Azure. ✔ Real-World Scenarios: Practical examples and case studies that showcase how Azure AI is used to solve real business challenges, making learning both engaging and relevant. ✔ Exam-Ready Preparation: Thorough coverage of AI-102 exam objectives, complete with practice questions and expert tips to ensure you're well-prepared for exam day. ✔ Proven Expertise: Authored by Azure AI professionals who hold the certification and have hands-on experience in developing AI solutions, offering you invaluable insights and practical guidance. Whether you aspire to advance your career, validate your expertise, or simply become a proficient Azure AI Engineer, "Microsoft Certified Exam Guide - Azure AI Engineer Associate (AI-102)" is your trusted companion on this journey. Don't miss this opportunity to become a sought-after AI expert in a competitive job market. Prepare, practice, and succeed with the ultimate resource for AI-102 certification. Order your copy today and unlock a world of AI possibilities with Microsoft Azure! © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Download or read book Hands on Cloud Analytics with Microsoft Azure Stack written by Prashila Naik and published by BPB Publications. This book was released on 2020-11-12 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore and work with various Microsoft Azure services for real-time Data Analytics KEY FEATURESÊ Understanding what Azure can do with your data Understanding the analytics services offered by Azure Understand how data can be transformed to generate more data Understand what is done after a Machine Learning model is builtÊ Go through some Data Analytics real-world use cases ÊÊ DESCRIPTIONÊ Data is the key input for Analytics. Building and implementing data platforms such as Data Lakes, modern Data Marts, and Analytics at scale require the right cloud platform that Azure provides through its services. The book starts by sharing how analytics has evolved and continues to evolve. Following the introduction, you will deep dive into ingestion technologies. You will learn about Data processing services in Azure. You will next learn about what is meant by a Data Lake and understand how Azure Data Lake Storage is used for analytical workloads. You will then learn about critical services that will provide actual Machine Learning capabilities in Azure. The book also talks about Azure Data Catalog for cataloging, Azure AD for Access Management, Web Apps and PowerApps for cloud web applications, Cognitive services for Speech, Vision, Search and Language, Azure VM for computing and Data Science VMs, Functions as serverless computing, Kubernetes and Containers as deployment options. Towards the end, the book discusses two use cases on Analytics. WHAT WILL YOU LEARNÊÊ Explore and work with various Azure services Orchestrate and ingest data using Azure Data Factory Learn how to use Azure Stream Analytics Get to know more about Synapse Analytics and its features Learn how to use Azure Analysis Services and its functionalities Ê WHO THIS BOOK IS FORÊ This book is for anyone who has basic to intermediate knowledge of cloud and analytics concepts and wants to use Microsoft Azure for Data Analytics. This book will also benefit Data Scientists who want to use Azure for Machine Learning. Ê TABLE OF CONTENTSÊÊ 1. Ê Data and its power 2. Ê Evolution of Analytics and its Types 3. Ê Internet of Things 4. Ê AI and ML 5. Ê Why cloud 6. Ê What are a data lake and a modern datamart 7. Ê Introduction to Azure services 8. Ê Types of data 9. Ê Azure Data Factory 10. Stream Analytics 11. Azure Data Lake Store and Azure Storage 12. Cosmos DB 13.Ê Synapse Analytics 14.Ê Azure Databricks 15.Ê Azure Analysis Services 16.Ê Power BI 17.Ê Azure Machine Learning 18.Ê Sample Architectures and synergies - Real-Time and Batch 19.Ê Azure Data Catalog 20.Ê Azure Active Directory 21.Ê Azure Webapps 22.Ê Power apps 23.Ê Time Series Insights 24.Ê Azure Cognitive Services 25.Ê Azure Logicapps 26.Ê Azure VM 27.Ê Azure Functions 28.Ê Azure Containers 29.Ê Azure KubernetesÊ Service 30.Ê Use Case 1 31.Ê Use Case 2

Download or read book Exam Ref 70 775 Perform Data Engineering on Microsoft Azure HDInsight written by Raju Shreewastava and published by Microsoft Press. This book was released on 2018-05-22 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Direct from Microsoft, this Exam Ref is the official study guide for the Microsoft 70-775 Perform Data Engineering on Microsoft Azure HDInsight certification exam. Exam Ref 70-775 Perform Data Engineering on Microsoft Azure HDInsight offers professional-level preparation that helps candidates maximize their exam performance and sharpen their skills on the job. It focuses on the specific areas of expertise modern IT professionals need to successfully administer and provision HDInsight clusters, and implement effective Big Data processing solutions with HDInsight. Coverage includes: Deploy and configure HDInsight clusters, deploy and secure multi-user HDInsight clusters, ingest data for processing, and manage and debug HDInsight jobs Implement Big Data batch solutions with Hive and Apache Pig, design batch ETL solutions with Spark, and operationalize Hadoop and Spark Create and implement interactive queries with Spark SQL and Interactive Hive; perform exploratory analyses with Spark SQL and Hive, Jupyter, and Apache Zeppelin; perform interactive processing with Apache Phoenix on HBase Implement real-time processing: create Spark streaming applications (including structured streaming); leverage Apache Storm, Kafka, and HBase Microsoft Exam Ref publications stand apart from third-party study guides because they: Provide guidance from Microsoft, the creator of Microsoft certification exams Target IT professional-level exam candidates with content focused on their needs, not "one-size-fits-all" content Streamline study by organizing material according to the exam's objective domain (OD), covering one functional group and its objectives in each chapter Feature Thought Experiments to guide candidates through a set of "what if?" scenarios, and prepare them more effectively for Pro-level style exam questions Explore big picture thinking around the planning and design aspects of the IT pro's job role This is one of two exams required to earn the MCSA Data Engineering with Azure certification. (The second is Exam 70-776 Perform Big Data Engineering on Microsoft Cloud Services.)