TPOT is an open-source AutoML library that automates the entire machine learning pipeline, from feature selection to model selection and hyperparameter tuning. By leveraging genetic programming, TPOT efficiently searches through a wide range of machine learning pipelines to find the most effective model for a given task.

MLflow is an open-source platform that manages the end-to-end machine learning lifecycle. It includes tools for tracking experiments, packaging code into reproducible runs, and sharing and deploying models.

Auto-sklearn is an extension of the popular Scikit-learn library, focusing on automating the machine learning pipeline. It employs Bayesian optimization to efficiently explore the hyperparameter space, delivering competitive models without the need for exhaustive manual tuning.

AutoKeras is an AutoML library specifically designed for neural network architecture search. It automates the process of designing and optimizing deep learning models, making it an ideal choice for practitioners seeking efficient solutions for image and text-based tasks.