Machine learning (ML)

Machine learning is a sub-area of artificial intelligence (AI). It enables computers to learn and become more efficient without having to be explicitly programmed. This gives machines the ability to examine data, determine trends and adapt independently to circumstances. ML learns from data and experience. This allows processes to be improved, patterns in business processes to be recognized and decisions to be made

 

The most important areas of machine learning

• Supervised learning: Models are trained using labeled data.
• Unsupervised learning: To recognize patterns, models are trained using unlabeled data.
• Reinforcement learning: An agent makes decisions and receives feedback.
• Semi-supervised learning: The combination of supervised and unsupervised learning.

Machine learning increases productivity and efficiency by automating repetitive tasks. This transforms business processes and creates space for creative solutions. Teams can focus more on strategic and creative challenges. Automated learning not only maximizes resource utilization, but also creates opportunities for in-depth analytical solutions.

Further links:

Connected Workers: Ein Leitfaden für den digitalen Wandel am Shopfloor.