Predicting Car Prices Using K-Nearest Neighbors¶

This project offers a description of how the K-Nearest Neighbors algorithm works. We will apply it to a real world dataset, after performing some cleaning. The main goal is to get a grasp of how we can train a model, improve its functioning through the development of certain tools, and use it to make predictions.

• To read the analysis open K_Nearest_Neighbor_Basics.ipynb

Required Libraries used within the project

The project is written in Python, using the following tools:

• Pandas
• Numpy
• Sklearn
• Matplotlib
• Seaborn