AutoML - A Short Overview: Why AutoML Is Ready To Be The Future Of Artificial Intelligence

When businesses identify a problem which can be solved by machine learning, they brief the data analysts and scientists to create a predictive analytics solution. In many cases, the turnaround period for delivering a solution is quite long. Even for seasoned data scientists, switching machine learning models that can accurately forecast the outcomes is always challenging and time-consuming. The complex workflow involved in machine learning units have several stages. Some of the substantial measures include data acquisition, information mining, feature engineering, design selection, experimentation and prediction.