Machine learning concern methods to find patterns in data. Supervised learning assumes the availability of labels or values. Models predict those for new data. Unsupervised learning finds patterns in data without labels.

The machine learning process typically includes five steps:

1. data representation
2. model selection
3. objective definition
4. optimization
5. validation

CC AIM focusses on time series and natural language data. Besides, we research optimization.