AutoML involves the partial or complete automation of the machine learning application. A well known example is Google Cloud AutoML service, which allows developers to train machine learning models without the need of prior technical knowledge. The service is based on a simple and intuitive drag and drop interface.
Why is autoML important ?
- It increases productivity by automating repetitive tasks. This enables the data scientist to focus more on the problem rather than on the models themselves
- Automating the ML pipeline also helps to avoid manual errors
- It is a step towards democratizing machine learning by making it accessible to everybody