What is overfitting and how do you avoid it?

• Overfitting means the machine learning model performed very well on the training data but does not generalize well.

• This happens when the model is very complex compared to the amount and noise of the training dataset.

• Here are some of the steps you can take to avoid overfitting:

1. Simplify the machine learning model by selecting one of the fewer parameters by reducing the number of features in the training dataset or by constraining the model.

2. Collect more training data, and if you have a limited amount of data, increase the size of the training data.

3. Remove outliers and explore your data further to correct more data errors.