How It Works ยท Technology
Machine Learning
Models that learn from data
Machine learning trains models on labeled or unlabeled data, adjusting parameters to minimize error, then infers on new inputs.
- training data
- features
- model
- loss function
- inference
Inputs
Data with features and, for supervised tasks, target labels.
Process
Algorithms adjust parameters to reduce loss via optimization such as gradient descent.
Outputs
A model that generalizes patterns to predict or classify new data.