# Introduction The L1-Logistic Regression model is a binary classification method that uses L1 regularization to induce sparsity in the model. The regularization path of this model shows the coefficients of the model as regularization strength increases. In this lab, we will use the Iris dataset to train L1-penalized logistic regression models and plot their regularization paths. ## 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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