Automated Machine Learning: Methods, Systems, Challenges

Automated Machine Learning refers to the automation of the repetitive and time-consuming tasks involved in traditional machine learning workflows. It involves using algorithms and tools to automate tasks like dataset cleaning, algorithm selection, hyperparameter tuning, and model selection. The use of Automated Machine Learning can speed up the time to create and deploy machine learning models and make it more accessible to non-experts. However, there are still many challenges to overcome in the development of Automated Machine Learning, including scalability, interpretability, and fairness.