Azure Machine: A practical, step-by-step guide to using Microsoft’s AutoML technology by Borys Mcneil
English | 2022 | ISBN: N/A | ASIN: B0B4BLY5NX | 328 pages | EPUB | 29 Mb
An useful, step-by-step overview to using Microsoft’s AutoML innovation on the Azure Artificial intelligence solution for designers and also data researchers working with the Python shows language
Key Features
Produce, deploy, productionalize, as well as scale automated machine learning services on Microsoft Azure
Boost the accuracy of your ML designs through automatic data featurization as well as version training
Increase efficiency in your organization by using expert system to address typical troubles
Book Summary
Automated Equipment Learning with Microsoft Azure aids you to construct high-performing, accurate device learning models in record time. It permits any person to conveniently harness the power of artificial intelligence and also raise the productivity as well as productivity of your organization. With a series of click a directed user interface (GUI), novices and also skilled data researchers alike can train and release machine learning services to manufacturing with ease.
This publication will certainly show you how to utilize Azure AutoML with both the GUI as well as the AzureML Python software advancement set (SDK) in a mindful, step-by-step means. First, you’ll find out just how to prepare data, train designs, and also register them to your Azure Artificial intelligence work space. You’ll then uncover how to take those models as well as utilize them to develop both automated batch options making use of artificial intelligence pipelines as well as real-time racking up options making use of Azure Kubernetes Service (AKS). Ultimately, you will certainly be able to utilize AutoML on your own data to not only train regression, classification, as well as forecasting versions but likewise utilize them to solve a wide array of organization problems.
By the end of this Azure book, you’ll have the ability to reveal your company partners exactly how your ML versions are making forecasts through automatically created graphes and also graphs, making their trust fund and respect.
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