دانلود کتاب Microsoft Azure Essentials Azure Machine Learning

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Cover Microsoft Press Store Newsletters Microsoft Press Guided Tours app Table of Contents Foreword Introduction Who should read this book Assumptions This book might not be for you if… Organization of this book Conventions and features in this book System requirements Acknowledgments Errata, updates, & support Free ebooks from Microsoft Press Free training from Microsoft Virtual Academy We want to hear from you Stay in touch Chapter 1 Introduction to the science of data What is machine learning? Today's perfect storm for machine learning Predictive analytics Endless amounts of machine learning fuel Everyday examples of predictive analytics Early history of machine learning Science fiction becomes reality Summary Resources Chapter 2 Getting started with Azure Machine Learning Core concepts of Azure Machine Learning High-level workflow of Azure Machine Learning Azure Machine Learning algorithms Supervised learning Unsupervised learning Deploying a prediction model Show me the money The what, the how, and the why Summary Resources Chapter 3 Using Azure ML Studio Azure Machine Learning terminology Getting started Azure Machine Learning pricing and availability Create your first Azure Machine Learning workspace Create your first Azure Machine Learning experiment Download dataset from a public repository Upload data into an Azure Machine Learning experiment Create a new Azure Machine Learning experiment Visualizing the dataset Split up the dataset Train the model Selecting the column to predict Score the model Visualize the model results Evaluate the model Save the experiment Preparing the trained model for publishing as a web service Create scoring experiment Expose the model as a web service Azure Machine Learning web service BATCH execution Testing the Azure Machine Learning web service Publish to Azure Data Marketplace Overview of the publishing process Guidelines for publishing to Azure Data Marketplace Summary Chapter 4 Creating Azure Machine Learning client and server applications Why create Azure Machine Learning client applications? Azure Machine Learning web services sample code C# console app sample code R sample code Moving beyond simple clients Cross-Origin Resource Sharing and Azure Machine Learning web services Create an ASP.NET Azure Machine Learning web client Making it easier to test our Azure Machine Learning web service Validating the user input Create a web service using ASP.NET Web API Enabling CORS support Processing logic for the Web API web service Summary Chapter 5 Regression analytics Linear regression Azure Machine Learning linear regression example Download sample automobile dataset Upload sample automobile dataset Create automobile price prediction experiment Summary Resources Chapter 6 Cluster analytics Unsupervised machine learning Cluster analysis KNN: K nearest neighbor algorithm Clustering modules in Azure ML Studio Clustering sample: Grouping wholesale customers Operationalizing a K-means clustering experiment Summary Resources Chapter 7 The Azure ML Matchbox recommender Recommendation engines in use today Mechanics of recommendation engines Azure Machine Learning Matchbox recommender background Azure Machine Learning Matchbox recommender: Restaurant ratings Building the restaurant ratings recommender Creating a Matchbox recommender web service Summary Resources Chapter 8 Retraining Azure ML models Workflow for retraining Azure Machine Learning models Retraining models in Azure Machine Learning Studio Modify original training experiment Add an additional web endpoint Retrain the model via batch execution service Summary Resources About the Author Free ebooks Tell us what you think!