Batch learning:
Batch learning is a machine learning technique where the model is trained using the entire dataset provided. This means the model is trained on all the data points available at once, and the model is not updated with new data points as they become available. For example, a supervised learning algorithm that is trained on a dataset of customer data in order to predict customer churn.
Online learning:
Online learning is a machine learning technique where the model is trained incrementally on individual data points as they become available. This means the model is updated with new data points as they become available, and the model is continuously updated with new data points. For example, a supervised learning algorithm that is trained on a stream of customer data in order to predict customer churn.