What is Overfitting in Machine Learning and how can you avoid?

When a machine attempts to learn from an insufficient dataset, it is said to be overfitting. As a result, overfitting is proportional to the amount of data.

The cross-validation approach can be used to avoid overfitting in small datasets. We will partition the dataset into two pieces using this method. Testing and training sets will be included in these two parts. The training dataset will be used to train the model, and the testing dataset will be used to test the model for fresh inputs.

We can avoid overfitting by doing so.