Online Learning
Online learning is a machine learning paradigm where the model continuously learns from a stream of data, updating its parameters incrementally as new data arrives. Unlike batch learning, where the model is trained on a fixed dataset, online learning adapts to changes in data distributions over time without needing to retrain from scratch. This makes it suitable for dynamic environments and real-time applications.
It's like a student who learns one new concept at a time and integrates it immediately into their existing knowledge, rather than waiting for a whole textbook to be finished.
It allows AI systems to adapt in real-time to evolving data, remaining relevant and accurate without costly full retraining cycles.
Learn one new AI thing every day.
Daily Deck sends you seven plain-English cards like this every morning. Free.
Start free