AutoML refers to the use of automated processes and algorithms to automate various stages of the machine learning workflow.
It aims to simplify and accelerate the process of developing and deploying machine learning models.
AutoML tools automate tasks such as data preprocessing, feature engineering, model selection, hyperparameter tuning,etc.
It enables non-experts to leverage machine learning capabilities and reduces the entry barrier.
AutoML algorithms can automatically analyze and understand the characteristics of the data.
It helps in automating the selection of the most appropriate machine learning algorithms based on the specific problem and dataset.
AutoML enables efficient use of computational resources by automating resource allocation and model training processes.
It promotes reproducibility and transparency by automating the documentation and tracking of the entire machine learning pipeline.
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