# Introduction In machine learning, a pipeline is a series of steps that are performed sequentially to transform the input data and then build a model. Scikit-learn provides a pipeline class that can be used to chain multiple processing steps together, making it easy to build complex models that involve multiple preprocessing and modeling steps. In this tutorial, we will demonstrate how to build a pipeline with feature selection and SVM classification using Scikit-learn. We will show how to integrate feature selection within the pipeline to prevent overfitting, and how to inspect the pipeline to better understand the model. ## 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.
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