# Introduction Nearest Neighbors Regression is a machine learning algorithm that predicts the value of a new data point by finding the k-nearest data points in the training set and using their average value to predict the new value. In this lab, we will use scikit-learn to demonstrate how to resolve a regression problem using a k-Nearest Neighbor and the interpolation of the target using both barycenter and constant weights. ## 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