What is preprocessing in scikit-learn?

What is preprocessing in scikit-learn?

Preprocessing in scikit-learn involves transforming raw data into a format suitable for modeling, such as scaling or encoding.

Why is preprocessing important for machine learning?

Preprocessing is crucial because it helps improve model accuracy, ensures data quality, and enhances the learning process.

Can you give me examples of preprocessing techniques?

Sure! Common techniques include normalization, standardization, one-hot encoding, and handling missing values.

How do I implement preprocessing in my scikit-learn project?

You can use classes like StandardScaler, MinMaxScaler, and OneHotEncoder from sklearn.preprocessing to implement these techniques.