Machine learning is a generic term for the “artificial” generation of knowledge from experience: An artificial system learns from examples and can generalize these after completion of the learning phase. That is, the examples are not simply memorized, but “recognize” patterns and laws in the learning data. Thus, the system can also assess unknown data (learning transfer) or fail to learn unknown data.