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Copyright (c) Microsoft Corporation Copyright (c) Microsoft Corporation
<br/>Licensed under the MIT License <br/>Licensed under the MIT License
# Auto Brew ML
# Overview # Overview
Traditional machine learning model development is resource-intensive, requiring significant domain/statistical knowledge and time to produce and compare dozens of models. Traditional machine learning model development is resource-intensive, requiring significant domain/statistical knowledge and time to produce and compare dozens of models.
With automated machine learning, the time it takes to get production-ready ML models with great ease and efficiency highly accelerates. However, the Automated Machine Learning does not yet provide much in terms of data preparation and feature engineering. With automated machine learning, the time it takes to get production-ready ML models with great ease and efficiency highly accelerates. However, the Automated Machine Learning does not yet provide much in terms of data preparation and feature engineering.