Examples of Overfitting and Underfitting

AI • Machine Learning • Tech on Instagram: "Overfitting happens when a model learns the training data too closely, including its noise or random fluctuations, instead of capturing the general pattern. Imagine you’re fitting curves to a set of data points that roughly follow a parabolic trend. A linear model (a straight line) is too simple — it underfits because it can’t capture the curve, leading to both high training and test errors. A quadratic model (a simple parabola) matches the data’s true

What Is Overfitting vs. Underfitting? | IBM

Overfitting and Underfitting

Bias vs variance explained: Avoid overfitting in ML