Machine Learning, Illustrated: Incremental Learning
Welcome back to the Illustrated Machine Learning series. If you read the other articles in the series, you know the drill. We take a (boring sounding) machine learning concept and make it fun by illustrating it! This article will cover a concept called Incremental Learning, where machine learning models learn new information over time, maintaining and building upon previous knowledge. But before getting into that, let’s first talk about what the model building process looks like today.
We usually follow a process called static learning when building models. In this process, we train a model using the latest available data. We tweak and tune the model in the training process. And once we’re happy with its performance, we deploy it. This model is in production for a while. Then we notice that the model performance is getting worse over time. That’s when we throw away the existing model and build a new one using the latest available data. And we rinse and repeat this same process.
0 Comments