Learn what is automated ML or AutoML in Azure Machine Learning, how it works, what are its benefits, and how to use it for various machine learning tasks.
Table of Contents
Question
Azure Machine Learning includes an automated machine learning capability that leverages the scalability of cloud compute to automatically try multiple pre-processing techniques and model-training algorithms in parallel to find the best performing supervised machine learning model for your data. True or False?
A. True
B. False
Answer
A. True
Explanation
Azure Machine Learning includes an automated machine learning capability that leverages the scalability of cloud compute to automatically try multiple pre-processing techniques and model-training algorithms in parallel to find the best performing supervised machine learning model for your data.
The correct answer is A. True.
Azure Machine Learning includes an automated machine learning capability that leverages the scalability of cloud compute to automatically try multiple pre-processing techniques and model-training algorithms in parallel to find the best performing supervised machine learning model for your data. This is also known as automated ML or AutoML.
Automated ML empowers users, with or without data science expertise, to identify an end-to-end machine learning pipeline for any problem, achieving a high quality machine learning model while spending far less of their time. Automated ML in Azure Machine Learning is based on a breakthrough from our Microsoft Research division.
Automated ML supports a variety of machine learning tasks, such as classification, regression, forecasting, computer vision, and natural language processing. Users can choose whether they want a code-first experience or a no-code studio web experience to build and deploy their models. Automated ML also provides transparency and trust in the models by using model interpretability and responsible machine learning solutions.
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