Machine Learning With Microsoft Technologies

Machine Learning With Microsoft Technologies Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Machine Learning With Microsoft Technologies book. This book definitely worth reading, it is an incredibly well-written.

Machine Learning with Microsoft Technologies

Author : Leila Etaati
Publisher : Apress
Page : 363 pages
File Size : 48,9 Mb
Release : 2019-06-12
Category : Computers
ISBN : 9781484236581

Get Book

Machine Learning with Microsoft Technologies by Leila Etaati Pdf

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 solutionCreate and manage Microsoft’s tool environments for development, testing, and production of a machine learning projectImplement 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.

Microsoft Azure Essentials Azure Machine Learning

Author : Jeff Barnes
Publisher : Microsoft Press
Page : 336 pages
File Size : 54,5 Mb
Release : 2015-04-25
Category : Computers
ISBN : 9780735698185

Get Book

Microsoft Azure Essentials Azure Machine Learning by Jeff Barnes Pdf

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.

Microsoft Azure Machine Learning

Author : Sumit Mund
Publisher : Packt Publishing Ltd
Page : 212 pages
File Size : 43,6 Mb
Release : 2015-06-16
Category : Computers
ISBN : 9781784398514

Get Book

Microsoft Azure Machine Learning by Sumit Mund Pdf

This book provides you with the skills necessary to get started with Azure Machine Learning to build predictive models as quickly as possible, in a very intuitive way, whether you are completely new to predictive analysis or an existing practitioner. The book starts by exploring ML Studio, the browser-based development environment, and explores the first step—data exploration and visualization. You will then build different predictive models using both supervised and unsupervised algorithms, including a simple recommender system. The focus then shifts to learning how to deploy a model to production and publishing it as an API. The book ends with a couple of case studies using all the concepts and skills you have learned throughout the book to solve real-world problems.

Hands-On Machine Learning with Azure

Author : Thomas K Abraham,Parashar Shah,Jen Stirrup,Lauri Lehman,Anindita Basak
Publisher : Packt Publishing Ltd
Page : 340 pages
File Size : 44,9 Mb
Release : 2018-10-31
Category : Computers
ISBN : 9781789130270

Get Book

Hands-On Machine Learning with Azure by Thomas K Abraham,Parashar Shah,Jen Stirrup,Lauri Lehman,Anindita Basak Pdf

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

Automated Machine Learning with Microsoft Azure

Author : Dennis Michael Sawyers
Publisher : Packt Publishing Ltd
Page : 340 pages
File Size : 43,8 Mb
Release : 2021-04-23
Category : Computers
ISBN : 9781800561977

Get Book

Automated Machine Learning with Microsoft Azure by Dennis Michael Sawyers Pdf

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.

Introducing Machine Learning

Author : Dino Esposito,Francesco Esposito
Publisher : Microsoft Press
Page : 616 pages
File Size : 51,5 Mb
Release : 2020-01-31
Category : Computers
ISBN : 9780135588383

Get Book

Introducing Machine Learning by Dino Esposito,Francesco Esposito Pdf

Master machine learning concepts and develop real-world solutions Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft’s powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilizing neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning. · 14-time Microsoft MVP Dino Esposito and Francesco Esposito help you · Explore what’s known about how humans learn and how intelligent software is built · Discover which problems machine learning can address · Understand the machine learning pipeline: the steps leading to a deliverable model · Use AutoML to automatically select the best pipeline for any problem and dataset · Master ML.NET, implement its pipeline, and apply its tasks and algorithms · Explore the mathematical foundations of machine learning · Make predictions, improve decision-making, and apply probabilistic methods · Group data via classification and clustering · Learn the fundamentals of deep learning, including neural network design · Leverage AI cloud services to build better real-world solutions faster About This Book · For professionals who want to build machine learning applications: both developers who need data science skills and data scientists who need relevant programming skills · Includes examples of machine learning coding scenarios built using the ML.NET library

Mastering Azure Machine Learning

Author : Christoph Körner,Kaijisse Waaijer
Publisher : Packt Publishing Ltd
Page : 437 pages
File Size : 54,5 Mb
Release : 2020-04-30
Category : Computers
ISBN : 9781789801521

Get Book

Mastering Azure Machine Learning by Christoph Körner,Kaijisse Waaijer Pdf

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.

Predictive Analytics with Microsoft Azure Machine Learning

Author : Valentine Fontama,Roger Barga,Wee Hyong Tok
Publisher : Apress
Page : 178 pages
File Size : 52,8 Mb
Release : 2014-11-25
Category : Computers
ISBN : 9781484204450

Get Book

Predictive Analytics with Microsoft Azure Machine Learning by Valentine Fontama,Roger Barga,Wee Hyong Tok Pdf

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.

Machine Learning with Dynamics 365 and Power Platform

Author : Aurelien Clere,Vinnie Bansal
Publisher : John Wiley & Sons
Page : 247 pages
File Size : 43,6 Mb
Release : 2022-01-06
Category : Computers
ISBN : 9781119771296

Get Book

Machine Learning with Dynamics 365 and Power Platform by Aurelien Clere,Vinnie Bansal Pdf

Apply cutting-edge AI techniques to your Dynamics 365 environment to create new solutions to old business problems In Machine Learning with Dynamics 365 and Power Platform: The Ultimate Guide to Apply Predictive Analytics, an accomplished team of digital and data analytics experts delivers a practical and comprehensive discussion of how to integrate AI Builder with Dataverse and Dynamics 365 to create real-world business solutions. It also walks you through how to build powerful machine learning models using Azure Data Lake, Databricks, Azure Synapse Analytics. The book is filled with clear explanations, visualizations, and working examples that get you up and running in your development of supervised, unsupervised, and reinforcement learning techniques using Microsoft machine learning tools and technologies. These strategies will transform your business verticals, reducing costs and manual processes in finance and operations, retail, telecommunications, and manufacturing industries. The authors demonstrate: What machine learning is all about and how it can be applied to your organization's Dynamics 365 and Power Platform Projects The creation and management of environments for development, testing, and production of a machine learning project How adopting machine learning techniques will redefine the future of your ERP/CRM system Perfect for Technical Consultants, software developers, and solution architects, Machine Learning with Dynamics 365 and Power Platform is also an indispensable guide for Chief Technology Officers seeking an intuitive resource for how to implement machine learning in modern business applications to solve real-world problems.

Deep Learning with Azure

Author : Mathew Salvaris,Danielle Dean,Wee Hyong Tok
Publisher : Apress
Page : 298 pages
File Size : 40,6 Mb
Release : 2018-08-24
Category : Computers
ISBN : 9781484236796

Get Book

Deep Learning with Azure by Mathew Salvaris,Danielle Dean,Wee Hyong Tok Pdf

Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI? Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll Learn Become familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AI Use pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more) Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolving Discover the options for training and operationalizing deep learning models on Azure Who This Book Is For Professional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful.

Pattern Recognition and Machine Learning

Author : Christopher M. Bishop
Publisher : Springer
Page : 0 pages
File Size : 50,8 Mb
Release : 2016-08-23
Category : Computers
ISBN : 1493938436

Get Book

Pattern Recognition and Machine Learning by Christopher M. Bishop Pdf

This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Practical Automated Machine Learning on Azure

Author : Deepak Mukunthu,Parashar Shah,Wee Hyong Tok
Publisher : "O'Reilly Media, Inc."
Page : 198 pages
File Size : 42,6 Mb
Release : 2019-09-23
Category : Computers
ISBN : 9781492055549

Get Book

Practical Automated Machine Learning on Azure by Deepak Mukunthu,Parashar Shah,Wee Hyong Tok Pdf

Develop smart applications without spending days and weeks building machine-learning models. With this practical book, you’ll learn how to apply automated machine learning (AutoML), a process that uses machine learning to help people build machine learning models. Deepak Mukunthu, Parashar Shah, and Wee Hyong Tok provide a mix of technical depth, hands-on examples, and case studies that show how customers are solving real-world problems with this technology. Building machine-learning models is an iterative and time-consuming process. Even those who know how to create ML models may be limited in how much they can explore. Once you complete this book, you’ll understand how to apply AutoML to your data right away. Learn how companies in different industries are benefiting from AutoML Get started with AutoML using Azure Explore aspects such as algorithm selection, auto featurization, and hyperparameter tuning Understand how data analysts, BI professions, developers can use AutoML in their familiar tools and experiences Learn how to get started using AutoML for use cases including classification, regression, and forecasting.

Automatic Speech Recognition

Author : Dong Yu,Li Deng
Publisher : Springer
Page : 329 pages
File Size : 50,8 Mb
Release : 2014-11-11
Category : Technology & Engineering
ISBN : 9781447157793

Get Book

Automatic Speech Recognition by Dong Yu,Li Deng Pdf

This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.

Deep Learning

Author : Li Deng,Dong Yu
Publisher : Unknown
Page : 212 pages
File Size : 43,5 Mb
Release : 2014
Category : Machine learning
ISBN : 1601988141

Get Book

Deep Learning by Li Deng,Dong Yu Pdf

Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks

Interpretable Machine Learning

Author : Christoph Molnar
Publisher : Lulu.com
Page : 320 pages
File Size : 52,7 Mb
Release : 2020
Category : Artificial intelligence
ISBN : 9780244768522

Get Book

Interpretable Machine Learning by Christoph Molnar Pdf

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.