Pipelines and Composite Estimators

# Introduction

In scikit-learn, pipelines and composite estimators are used to combine multiple transformers and estimators into a single model. This is useful when there is a fixed sequence of steps for processing the data, such as feature selection, normalization, and classification. Pipelines can also be used for joint parameter selection and to ensure that statistics from the test data do not leak into the trained model during cross-validation.

## VM Tips

After the VM startup is done, click the top left corner to switch to the **Notebook** tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.