# Introduction In this lab, we will learn about neural network models and how they can be used in supervised learning tasks. Neural networks are a popular type of machine learning algorithm that can learn non-linear patterns in data. They are often used for classification and regression tasks. We will specifically focus on the Multi-layer Perceptron (MLP) algorithm, which is a type of neural network that has one or more hidden layers between the input and output layers. MLP can learn complex non-linear relationships in data, making it suitable for a wide range of tasks. ## 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.
Click the virtual machine below to start practicing