What is AutoML?

AutoML refers to the methodology of automating the process of building machine learning models, including data preprocessing, feature engineering, model selection, hyperparameter tuning, and model deployment. AutoML aims to make machine learning accessible and more efficient for non-experts, saving time and resources for experts by reducing the amount of manual work involved in building a model. Different types of AutoML products on the market offer different levels of automation. Some just automate the training and hyperparameter portion of it, while some do end-to-end automation by also automating the steps of data preprocessing and feature generation.

AutoML tools allow users to specify their requirements, such as accuracy, interpretability, or training time, and then automatically select and train the best model based on these criteria. It can be used for various types of machine learning tasks, including classification, regression, and time series forecasting...