Machine learning models

Definition

Machine learning models are computer programs that can learn from data and make predictions or decisions without being explicitly programmed. They use statistical techniques to identify patterns in data and generalize from them.

Related terms

Neural networks: These are specific types of machine learning models inspired by the structure of biological brains. They consist of interconnected nodes (neurons) organized into layers that process information.

Training data: This is the labeled dataset used to train a machine learning model. It consists of input examples paired with their corresponding correct outputs or labels.

Prediction/Inference: Once a machine learning model is trained, it can be used to make predictions or inferences on new, unseen data. This is the process of using the model to generate output based on input.