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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 Features Create, deploy, productionalize, and scale automated machine learning solutions on Microsoft Azure Improve the accuracy of your ML models through automatic data featurization and model training Increase productivity in your organization by using artificial intelligence to solve common problems Book 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 learn <
This book provides a practical, step-by-step guide to implementing automated machine learning solutions using Microsoft Azure's AutoML technology. The author, Dennis Michael Sawyers, aims to equip developers and data scientists with the skills to create, deploy, and scale AI solutions efficiently. It covers both GUI-based approaches and the AzureML Python SDK, focusing on data preparation, model training, registration, and deployment for batch and real-time scoring. The book emphasizes demonstrating model predictions through automatically generated visualizations to build trust with business stakeholders.
The book is presented as a practical guide for professionals looking to implement AI solutions on Azure. Its focus on step-by-step instructions and the use of both GUI and SDK methods suggests it aims to be accessible to a range of technical users. The emphasis on demonstrating model predictions through visualizations indicates a goal of fostering trust and understanding between technical teams and business stakeholders. The content appears geared towards improving efficiency and profitability through the application of machine learning.
Page Count:
340
Publication Date:
2021-04-23
Publisher:
Packt Publishing
ISBN-10:
1800561970
ISBN-13:
9781800561977
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