From the course: Machine Learning and AI Foundations: Value Estimations
Join today to access over 22,600 courses taught by industry experts or purchase this course individually.
Overfitting and underfitting
From the course: Machine Learning and AI Foundations: Value Estimations
Overfitting and underfitting
- [Instructor] A key challenge when building machine learning models is learning how to deal with underfitting and overfitting. Let's look at a graph of house prices where the value of each house is determined only based on the size of the house. A good model can predict prices by following the smooth curve. This curve follows the trend in the data. overfitting is when your model memorizes your exact training data, but doesn't actually figure out the pattern in the data. An overfit model might predict prices following a line like this. In other words, the model fits the training data too much. It will make bad predictions for any house that wasn't in the training data set. The problem is that the model doesn't generalize to the underlying trend. It just memorize these exact data points. underfitting is the opposite. It's when your model is too simple, and doesn't fully learn the pattern in the data. Here's an example of an underfit model. In this case, the model sort of works for…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.