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Automated Machine Learning with Microsoft Azure. Build highly accurate and scalable end-to-end AI solutions with Azure AutoML

Język publikacji: angielskim
Automated Machine Learning with Microsoft Azure. Build highly accurate and scalable end-to-end AI solutions with Azure AutoML Dennis Michael Sawyers - okladka książki

Automated Machine Learning with Microsoft Azure. Build highly accurate and scalable end-to-end AI solutions with Azure AutoML Dennis Michael Sawyers - okladka książki

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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.

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O autorze książki

Dennis Michael Sawyers is a senior cloud solutions architect (CSA) at Microsoft, specializing in data and AI. In his role as a CSA, he helps Fortune 500 companies leverage Microsoft Azure cloud technology to build top-class machine learning and AI solutions. Prior to his role at Microsoft, he was a data scientist at Ford Motor Company in Global Data Insight and Analytics (GDIA) and a researcher in anomaly detection at the highly regarded Carnegie Mellon Auton Lab. He received a master's degree in data analytics from Carnegie Mellon's Heinz College and a bachelor's degree from the University of Michigan. More than anything, Dennis is passionate about democratizing AI solutions through automated machine learning technology.

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