Machine Learning With Microsoft Technologies

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Machine Learning With Microsoft Technologies

Author : Leila Etaati
ISBN : 9781484236581
Genre : Computers
File Size : 47.8 MB
Format : PDF, Kindle
Download : 451
Read : 1237

Know how to do machine learning with Microsoft technologies. This book teaches you to do predictive, descriptive, and prescriptive analyses with Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, HD Insight, and more. The ability to analyze massive amounts of real-time data and predict future behavior of an organization is critical to its long-term success. Data science, and more specifically machine learning (ML), is today’s game changer and should be a key building block in every company’s strategy. Managing a machine learning process from business understanding, data acquisition and cleaning, modeling, and deployment in each tool is a valuable skill set. Machine Learning with Microsoft Technologies is a demo-driven book that explains how to do machine learning with Microsoft technologies. You will gain valuable insight into designing the best architecture for development, sharing, and deploying a machine learning solution. This book simplifies the process of choosing the right architecture and tools for doing machine learning based on your specific infrastructure needs and requirements. Detailed content is provided on the main algorithms for supervised and unsupervised machine learning and examples show ML practices using both R and Python languages, the main languages inside Microsoft technologies. What You'll Learn Choose the right Microsoft product for your machine learning solution Create and manage Microsoft’s tool environments for development, testing, and production of a machine learning project Implement and deploy supervised and unsupervised learning in Microsoft products Set up Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, and HD Insight to perform machine learning Set up a data science virtual machine and test-drive installed tools, such as Azure ML Workbench, Azure ML Server Developer, Anaconda Python, Jupyter Notebook, Power BI Desktop, Cognitive Services, machine learning and data analytics tools, and more Architect a machine learning solution factoring in all aspects of self service, enterprise, deployment, and sharing Who This Book Is For Data scientists, data analysts, developers, architects, and managers who want to leverage machine learning in their products, organization, and services, and make educated, cost-saving decisions about their ML architecture and tool set.
Category: Computers

Mastering Azure Machine Learning

Author : Christoph Körner
ISBN : 9781789801521
Genre : Computers
File Size : 54.20 MB
Format : PDF, ePub, Mobi
Download : 780
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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 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 learn Setup your Azure Machine Learning 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 Machine Learning Use hyperparameter tuning and Azure Automated Machine Learning to optimize your ML models Employ distributed ML on GPU clusters using Horovod in Azure Machine Learning 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 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.
Category: Computers

Beginning Security With Microsoft Technologies

Author : Vasantha Lakshmi
ISBN : 9781484248539
Genre : Computers
File Size : 49.64 MB
Format : PDF, ePub, Mobi
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Secure and manage your Azure cloud infrastructure, Office 365, and SaaS-based applications and devices. This book focuses on security in the Azure cloud, covering aspects such as identity protection in Azure AD, network security, storage security, unified security management through Azure Security Center, and many more. Beginning Security with Microsoft Technologies begins with an introduction to some common security challenges and then discusses options for addressing them. You will learn about Office Advanced Threat Protection (ATP), the importance of device-level security, and about various products such as Device Guard, Intune, Windows Defender, and Credential Guard. As part of this discussion you’ll cover how secure boot can help an enterprise with pre-breach scenarios. Next, you will learn how to set up Office 365 to address phishing and spam, and you will gain an understanding of how to protect your company's Windows devices. Further, you will also work on enterprise-level protection, including how advanced threat analytics aids in protection at the enterprise level. Finally, you’ll see that there are a variety of ways in which you can protect your information. After reading this book you will be able to understand the security components involved in your infrastructure and apply methods to implement security solutions. What You Will Learn Keep corporate data and user identities safe and secure Identify various levels and stages of attacks Safeguard information using Azure Information Protection, MCAS, and Windows Information Protection, regardless of your location Use advanced threat analytics, Azure Security Center, and Azure ATP Who This Book Is For Administrators who want to build secure infrastructure at multiple levels such as email security, device security, cloud infrastructure security, and more.
Category: Computers

Microsoft Azure Essentials Azure Machine Learning

Author : Jeff Barnes
ISBN : 9780735698185
Genre : Computers
File Size : 87.40 MB
Format : PDF, ePub, Docs
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Read : 767

Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the Microsoft Azure Essentials series.
Category: Computers

Exam Ref 70 774 Perform Cloud Data Science With Azure Machine Learning

Author : Ginger Grant
ISBN : 9780134849683
Genre : Computers
File Size : 76.36 MB
Format : PDF, ePub, Docs
Download : 291
Read : 850

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:
Category: Computers

C Machine Learning Projects

Author : Yoon Hyup Hwang
ISBN : 9781788996587
Genre : Computers
File Size : 71.87 MB
Format : PDF, Mobi
Download : 475
Read : 834

Power your C# and .NET applications with exciting machine learning models and modular projects Key Features Produce classification, regression, association, and clustering models Expand your understanding of machine learning and C# Get to grips with C# packages such as, LiveCharts, and Deedle Book Description Machine learning is applied in almost all kinds of real-world surroundings and industries, right from medicine to advertising; from finance to scientifc research. This book will help you learn how to choose a model for your problem, how to evaluate the performance of your models, and how you can use C# to build machine learning models for your future projects. You will get an overview of the machine learning systems and how you, as a C# and .NET developer, can apply your existing knowledge to the wide gamut of intelligent applications, all through a project-based approach. You will start by setting up your C# environment for machine learning with the required packages, Accord.NET, LiveCharts, and Deedle. We will then take you right from building classifcation models for spam email fltering and applying NLP techniques to Twitter sentiment analysis, to time-series and regression analysis for forecasting foreign exchange rates and house prices, as well as drawing insights on customer segments in e-commerce. You will then build a recommendation model for music genre recommendation and an image recognition model for handwritten digits. Lastly, you will learn how to detect anomalies in network and credit card transaction data for cyber attack and credit card fraud detections. By the end of this book, you will be putting your skills in practice and implementing your machine learning knowledge in real projects. What you will learn Set up the C# environment for machine learning with required packages Build classification models for spam email filtering Get to grips with feature engineering using NLP techniques for Twitter sentiment analysis Forecast foreign exchange rates using continuous and time-series data Make a recommendation model for music genre recommendation Familiarize yourself with munging image data and Neural Network models for handwritten-digit recognition Use Principal Component Analysis (PCA) for cyber attack detection One-Class Support Vector Machine for credit card fraud detection Who this book is for If you're a C# or .NET developer with good knowledge of C#, then this book is perfect for you to get Machine Learning into your projects and make smarter applications.
Category: Computers

Hands On Machine Learning With Azure

Author : Thomas K Abraham
ISBN : 9781789130270
Genre : Computers
File Size : 26.86 MB
Format : PDF, ePub, Mobi
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Read : 181

Implement machine learning, cognitive services, and artificial intelligence solutions by leveraging Azure cloud technologies Key Features Learn advanced concepts in Azure ML and the Cortana Intelligence Suite architecture Explore ML Server using SQL Server and HDInsight capabilities Implement various tools in Azure to build and deploy machine learning models Book 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 learn Discover the benefits of leveraging the cloud for ML and AI Use Cognitive Services APIs to build intelligent bots Build a model using canned algorithms from Microsoft and deploy it as a web service Deploy virtual machines in AI development scenarios Apply R, Python, SQL Server, and Spark in Azure Build and deploy deep learning solutions with CNTK, MMLSpark, and TensorFlow Implement model retraining in IoT, Streaming, and Blockchain solutions Explore best practices for integrating ML and AI functions with ADLA and logic apps Who 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
Category: Computers

Data Lake Analytics On Microsoft Azure

Author : Harsh Chawla
ISBN : 1484262514
Genre : Computers
File Size : 21.27 MB
Format : PDF, ePub
Download : 463
Read : 418

Get a 360-degree view of how the journey of data analytics solutions has evolved from monolithic data stores and enterprise data warehouses to data lakes and modern data warehouses. You will This book includes comprehensive coverage of how: To architect data lake analytics solutions by choosing suitable technologies available on Microsoft Azure The advent of microservices applications covering ecommerce or modern solutions built on IoT and how real-time streaming data has completely disrupted this ecosystem These data analytics solutions have been transformed from solely understanding the trends from historical data to building predictions by infusing machine learning technologies into the solutions Data platform professionals who have been working on relational data stores, non-relational data stores, and big data technologies will find the content in this book useful. The book also can help you start your journey into the data engineer world as it provides an overview of advanced data analytics and touches on data science concepts and various artificial intelligence and machine learning technologies available on Microsoft Azure. What Will You Learn You will understand the: Concepts of data lake analytics, the modern data warehouse, and advanced data analytics Architecture patterns of the modern data warehouse and advanced data analytics solutions Phases—such as Data Ingestion, Store, Prep and Train, and Model and Serve—of data analytics solutions and technology choices available on Azure under each phase In-depth coverage of real-time and batch mode data analytics solutions architecture Various managed services available on Azure such as Synapse analytics, event hubs, Stream analytics, CosmosDB, and managed Hadoop services such as Databricks and HDInsight Who This Book Is For Data platform professionals, database architects, engineers, and solution architects
Category: Computers

Machine Learning Techniques For Adaptive Multimedia Retrieval Technologies Applications And Perspectives

Author : Wei, Chia-Hung
ISBN : 9781616928612
Genre : Computers
File Size : 76.68 MB
Format : PDF, ePub, Mobi
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"This book disseminates current information on multimedia retrieval, advancing the field of multimedia databases, and educating the multimedia database community on machine learning techniques for adaptive multimedia retrieval research, design and applications"--Provided by publisher.
Category: Computers

Machine Learning For Decision Makers

Author : Patanjali Kashyap
ISBN : 9781484229880
Genre : Computers
File Size : 68.64 MB
Format : PDF
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Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other. This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making. The book uses case studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business. What You Will Learn Discover the machine learning, big data, and cloud and cognitive computing technology stack Gain insights into machine learning concepts and practices Understand business and enterprise decision-making using machine learning Absorb machine-learning best practices Who This Book Is For Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.
Category: Computers

Artificial Intelligence For Net Speech Language And Search

Author : Nishith Pathak
ISBN : 9781484229491
Genre : Computers
File Size : 37.80 MB
Format : PDF, ePub
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Get introduced to the world of artificial intelligence with this accessible and practical guide. Build applications that make intelligent use of language and user interaction to better compete in today’s marketplace. Discover how your application can deeply understand and interpret content on the web or a user’s machine, intelligently react to direct user interaction through speech or text, or make smart recommendations on products or services that are tailored to each individual user. With Microsoft Cognitive Services, you can do all this and more utilizing a set of easy-to-use APIs that can be consumed on the desktop, web, or mobile devices. Developers normally think of AI implementation as a tough task involving writing complex algorithms. This book aims to remove the anxiety by creating a cognitive application with a few lines of code. There is a wide range of Cognitive Services APIs available. This book focuses on some of the most useful and powerful ways that your application can make intelligent use of language. Artificial Intelligence for .NET: Speech, Language, and Search will show you how you can start building amazing capabilities into your applications today. What You'll Learn Understand the underpinnings of artificial intelligence through practical examples and scenarios Get started building an AI-based application in Visual Studio Build a text-based conversational interface for direct user interaction Use the Cognitive Services Speech API to recognize and interpret speech Look at different models of language, including natural language processing, and how to apply them in your Visual Studio application Reuse Bing search capabilities to better understand a user’s intention Work with recommendation engines and integrate them into your apps Who This Book Is For Developers working on a range of platforms, from .NET and Windows to mobile devices. Examples are given in C#. No prior experience with AI techniques or theory is required.
Category: Computers

Machine Learning In Cyber Trust

Author : Jeffrey J. P. Tsai
ISBN : 9780387887357
Genre : Computers
File Size : 62.84 MB
Format : PDF, Mobi
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Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information. Not surprisingly, the field of cyber-based systems is a fertile ground where many tasks can be formulated as learning problems and approached in terms of machine learning algorithms. This book contains original materials by leading researchers in the area and covers applications of different machine learning methods in the reliability, security, performance, and privacy issues of cyber space. It enables readers to discover what types of learning methods are at their disposal, summarizing the state-of-the-practice in this significant area, and giving a classification of existing work. Those working in the field of cyber-based systems, including industrial managers, researchers, engineers, and graduate and senior undergraduate students will find this an indispensable guide in creating systems resistant to and tolerant of cyber attacks.
Category: Computers

Artificial Intelligence And Deep Learning For Decision Makers

Author : Dr. Jagreet Kaur
ISBN : 9789389328684
Genre : Computers
File Size : 54.85 MB
Format : PDF, Mobi
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Learn modern-day technologies from modern-day technical giants DESCRIPTION The aim of this book is to help the readers understand the concept of artificial intelligence and deep learning methods and implement them into their businesses and organizations. The first two chapters describe the introduction of the artificial intelligence and deep learning methods. In the first chapter, the concept of human thinking process, starting from the biochemical responses within the structure of neurons to the problem-solving steps through computational thinking skills are discussed. All chapters after the first two should be considered as the study of different technological and Artificial Intelligence giants of current age. These chapters are placed in a way that each chapter could be considered a separate study of a separate company, which includes the achievements of intelligent services currently provided by the company, discussion on the business model of the company towards the use of the deep learning technologies, the advancement of the web services which are incorporated with intelligent capability introduced by company, the efforts of the company in contributing to the development of the artificial intelligence and deep learning research. KEY FEATURES Real-world success and failure stories of artificial intelligence explained Understand concepts of artificial intelligence and deep learning methods Learn how to use artificial intelligence and deep learning methods Know how to prepare dataset and implement models using industry leading Python packages You’ll be able to apply and analyze the results produced by the models for prediction WHAT WILL YOU LEARN How to use the algorithms written in the Python programming language to design models and perform predictions in general datasets Understand use cases in different industries related to the implementation of artificial intelligence and deep learning methods Learn the use of potential ideas in artificial intelligence and deep learning methods to improve the operational processes or new products and how services can be produced based on the methods WHO THIS BOOK IS FOR This book is targeted to business and organization leaders, technology enthusiasts, professionals, and managers who seek knowledge of artificial intelligence and deep learning methods. Table of Contents Artificial Intelligence and Deep Learning Data Science for Business Analysis Decision Making Intelligent Computing Strategies By Google Cognitive Learning Services in IBM Watson Advancement web services by Baidu Improved Social Business by Facebook Personalized Intelligent Computing by Apple Cloud Computing Intelligent by Microsoft
Category: Computers

Adapting Information And Communication Technologies For Effective Education

Author : Tomei, Lawrence A.
ISBN : 9781599049250
Genre : Business & Economics
File Size : 26.8 MB
Format : PDF, ePub, Mobi
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Educational initiatives attempt to introduce or promote a culture of quality within education by raising concerns related to student learning, providing services related to assessment, professional development of teachers, curriculum and pedagogy, and influencing educational policy, in the realm of technology. Adapting Information and Communication Technologies for Effective Education addresses ICT assessment in universities, student satisfaction in management information system programs, factors that impact the successful implementation of a laptop program, student learning and electronic portfolios, and strategic planning for e-learning. Providing innovative research on several fundamental technology-based initiatives, this book will make a valuable addition to every reference library.
Category: Business & Economics

Hands On Cloud Analytics With Microsoft Azure Stack

Author : Prashila Naik
ISBN : 9789389898149
Genre : Computers
File Size : 36.77 MB
Format : PDF, Mobi
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Explore and work with various Microsoft Azure services for real-time Data Analytics KEY FEATURES 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 built Go through some Data Analytics real-world use cases DESCRIPTION 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 LEARN 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 WHO THIS BOOK IS FOR 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. TABLE OF CONTENTS 1. Data and its power 2. Evolution of Analytics and its Types 3. Internet of Things 4. AI and ML 5. Why cloud 6. What are a data lake and a modern datamart 7. Introduction to Azure services 8. Types of data 9. Azure Data Factory 10. Stream Analytics 11. Azure Data Lake Store and Azure Storage 12. Cosmos DB 13. Synapse Analytics 14. Azure Databricks 15. Azure Analysis Services 16. Power BI 17. Azure Machine Learning 18. Sample Architectures and synergies - Real-Time and Batch 19. Azure Data Catalog 20. Azure Active Directory 21. Azure Webapps 22. Power apps 23. Time Series Insights 24. Azure Cognitive Services 25. Azure Logicapps 26. Azure VM 27. Azure Functions 28. Azure Containers 29. Azure Kubernetes Service 30. Use Case 1 31. Use Case 2
Category: Computers

Microsoft Office For Ipad Step By Step

Author : Joan Lambert
ISBN : 9780735697034
Genre : Computers
File Size : 68.5 MB
Format : PDF
Download : 951
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The quick way to learn Microsoft Word, Excel, PowerPoint, and OneNote for iPad! This is learning made easy. Get productive fast with every Office for iPad app--plus OneNote, too! Jump in wherever you need answers--brisk lessons and colorful screen shots show you exactly what to do, step by step. Quickly create Word documents by tapping, typing, or dictating Organize and design professional documents of all kinds Visually analyze information in tables, charts, and PivotTables Deliver highly effective presentations in PowerPoint straight from your iPad Save and send PDFs, with or without Office 365 Use OneNote to capture and share everything from text to iPad photos Now in full color! Easy lessons for essential tasks Big full-color visuals Skill-building practice files Download your Step by Step practice files at:
Category: Computers

Data Science Solutions On Azure

Author : Julian Soh
ISBN : 1484264045
Genre : Computers
File Size : 47.72 MB
Format : PDF, Docs
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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. You'll 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. You'll also explore Azure Databricks and learn how to deploy, create and manage the same. In the final chapters you'll 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 You'll Learn 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 Who This Book Is For Data Scientists looking to deploy end-to-end solutions on Azure with latest tools and techniques.
Category: Computers

Microsoft Azure Essentials Fundamentals Of Azure

Author : Michael Collier
ISBN : 9780735697300
Genre : Computers
File Size : 72.35 MB
Format : PDF, Mobi
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Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. The first ebook in the series, Microsoft Azure Essentials: Fundamentals of Azure, introduces developers and IT professionals to the wide range of capabilities in Azure. The authors - both Microsoft MVPs in Azure - present both conceptual and how-to content for key areas, including: Azure Websites and Azure Cloud Services Azure Virtual Machines Azure Storage Azure Virtual Networks Databases Azure Active Directory Management tools Business scenarios Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the “Microsoft Azure Essentials” series.
Category: Computers

Mining User Generated Content

Author : Marie-Francine Moens
ISBN : 9781466557406
Genre : Computers
File Size : 66.93 MB
Format : PDF, Mobi
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Originating from Facebook, LinkedIn, Twitter, Instagram, YouTube, and many other networking sites, the social media shared by users and the associated metadata are collectively known as user generated content (UGC). To analyze UGC and glean insight about user behavior, robust techniques are needed to tackle the huge amount of real-time, multimedia, and multilingual data. Researchers must also know how to assess the social aspects of UGC, such as user relations and influential users. Mining User Generated Content is the first focused effort to compile state-of-the-art research and address future directions of UGC. It explains how to collect, index, and analyze UGC to uncover social trends and user habits. Divided into four parts, the book focuses on the mining and applications of UGC. The first part presents an introduction to this new and exciting topic. Covering the mining of UGC of different medium types, the second part discusses the social annotation of UGC, social network graph construction and community mining, mining of UGC to assist in music retrieval, and the popular but difficult topic of UGC sentiment analysis. The third part describes the mining and searching of various types of UGC, including knowledge extraction, search techniques for UGC content, and a specific study on the analysis and annotation of Japanese blogs. The fourth part on applications explores the use of UGC to support question-answering, information summarization, and recommendations.
Category: Computers

Soft Computing In Machine Learning

Author : Sang-Yong Rhee
ISBN : 9783319055336
Genre : Technology & Engineering
File Size : 33.41 MB
Format : PDF, Docs
Download : 402
Read : 760

As users or consumers are now demanding smarter devices, intelligent systems are revolutionizing by utilizing machine learning. Machine learning as part of intelligent systems is already one of the most critical components in everyday tools ranging from search engines and credit card fraud detection to stock market analysis. You can train machines to perform some things, so that they can automatically detect, diagnose, and solve a variety of problems. The intelligent systems have made rapid progress in developing the state of the art in machine learning based on smart and deep perception. Using machine learning, the intelligent systems make widely applications in automated speech recognition, natural language processing, medical diagnosis, bioinformatics, and robot locomotion. This book aims at introducing how to treat a substantial amount of data, to teach machines and to improve decision making models. And this book specializes in the developments of advanced intelligent systems through machine learning. It consists of 11 contributions that features illumination change detection, generator of electronic educational publications, intelligent call triage system, recognition of rocks at uranium deposits, graphics processing units, mathematical model of hit phenomena, selection and mutation in genetic algorithm, hands and arms motion estimation, application of wavelet network, Kanizsa triangle illusion, and support vector machine regression. Also, it describes how to apply the machine learning for the intelligent systems. This edition is published in original, peer reviewed contributions covering from initial design to final prototypes and verifications.
Category: Technology & Engineering