AutoML: Promises vs. Reality – IoT For All

Currently, selecting the "best" algorithm to use per dataset requires a level of intuition or expertise about the data. Data scientists leverage their experience to experiment with different combinations of models and hyperparameter values to achieve the highest accuracy. AutoML will lessen our dependency on intuition by iteratively trying out an algorithm, scoring its performance, and choosing and refining other models. In other words, it will automate the machine learning process of the data science work flow as we carefully defined above. There are other openly available tools such as Auto-sklearn for Python users and AutoWEKA for Weka users.