Machine Learning

Machine learning is a sub-area of artificial intelligence where systems can recognize patterns from data and predict or derive decisions without being explicitly programmed for each task.

Functionality and Use

Machine learning includes various methods of training AI systems based on data. Algorithms analyze large amounts of data, recognize connections and create models that can be used for predictions or automated decisions. Methods such as neural networks are often used. The quality and amount of training data is crucial, as they significantly influence how reliably the model will work later.

• Supervised learning: The model learns based on labeled training data with known input and output values.
• Unsupervised learning: The model independently recognizes patterns or structures in unstructured data.
• Reinforcement learning: A system learns to make optimal decisions by reward or punishment.

Examples

• Spam filter detects unwanted emails
• Recommendation system suggests products
• AI recognizes handwriting on documents
• Model predicts sales figures