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Fully build and productionize end-to-end machine learning solutions using Azure Machine Learning ServiceKey FeaturesAutomate complete machine learning solutions using Microsoft AzureUnderstand how to productionize machine learning modelsGet to grips with monitoring, MLOps, deep learning, distributed training, and reinforcement learningBook DescriptionData scientists working on productionizing machine learning (ML) workloads face a breadth of challenges at every step owing to the countless factors involved in getting ML models deployed and running. This book offers solutions to common issues, detailed explanations of essential concepts, and step-by-step instructions to productionize ML workloads using the Azure Machine Learning service. You'll see how data scientists and ML engineers working with Microsoft Azure can train and deploy ML models at scale by putting their knowledge to work with this practical guide. Throughout the book, you'll learn how to train, register, and productionize ML models by making use of the power of the Azure Machine Learning service. You'll get to grips with scoring models in real time and batch, explaining models to earn business trust, mitigating model bias, and developing solutions using an MLOps framework. By the end of this Azure Machine Learning book, you'll be ready to build and deploy end-to-end ML solutions into a production system using the Azure Machine Learning service for real-time scenarios.What you will learnTrain ML models in the Azure Machine Learning serviceBuild end-to-end ML pipelinesHost ML models on real-time scoring endpointsMitigate bias in ML modelsGet the hang of using an MLOps framework to productionize modelsSimplify ML model explainability using the Azure Machine Learning service and Azure InterpretWho this book is forMachine learning engineers and data scientists who want to move to ML engineering roles will find this AMLS book useful. Familiarity with the Azure ecosystem will assist with understanding the concepts covered.

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 languageKey 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 DescriptionAutomated 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 forData 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.

With her walk across America at the age of 90, New Hampshire native Doris Haddock entered the national consciousness as “Granny D,” a candid and feisty champion of commonsense populist politics. Four years later she ran for the U.S. Senate against the usual entrenched big-party interests—and lost. In the meantime, she became a cause célèbre, and an example of the kind of politics that puts people first. Granny D's American Century is the story of Doris Haddock both before and after these events: as a young woman whose bedrock New England values were tested during the Great Depression, and as a no-nonsense nonagenarian putting those values to work in the causes of voters'rights, women's rights, and campaign finance reform. Written in a clear, unsparing prose, Granny D's American Century is a warm reflection on a life well lived, and a clear and spirited call for virtue in American civic life.

Law Man is an improbable-but-true memoir of redemption -- the story of a young bank robber who became the greatest jailhouse lawyer in American history, and who changed not just his own life, but the lives of everyone around him. Shon Hopwood was a good kid from a good Nebraskan family, a small-town basketball star whose parents had started a local church. Few who knew him as a friendly teen would have imagined that, shortly after returning home from the Navy, he'd be adrift with few prospects and plotting to rob a bank. But rob he did, committing five heists before being apprehended. Only twenty three and potentially facing twelve years in Illinois'Pekin Federal Prison, Shon feared his life was already over. He'd shamed himself and his loving family and friends, and a part of him wanted to die. He wasn't sure at first if he'd survive the prison gangs, but slowly glimmers of hope appeared. He earned some respect on the prison basketball court, received a steady flow of letters from hometown well wishers, including a note from a special girl whom he'd thought too beautiful to ever pay him notice – and, most crucially, he secured a job in the prison law library. It was an assignment that would prove his salvation. Poring over the library's thick legal volumes, Shon discovered that he had a knack for the law, and he soon became the go-to guy for inmates seeking help. Then came a request to write a complex petition to the Supreme Court – a high-wire act of jailhouse lawyering that had never before met with success. By the time Shon walked out of Pekin Prison he'd pulled off a series of legal miracles, earned the undying gratitude of numerous inmates, won the woman of his dreams, and built a new life for himself far greater than anything he could have imagined. A story that mixes moments of high-adrenaline with others of deep poignancy, Law Man is a powerful reminder that even the worst mistakes can be redeemed through faith, hard work and the love and support of others.From the Hardcover edition.