Project 2

1. Load the Car Dataset.
2. Preprocessed the Data by handling missing values and scaling.
3. Applied K-Means Clustering to group the cars based on their features.
4. Predicted Classes based on cluster labels.

I used this approach so you can easily identify the types of cars and their respective features, aiding in decision-making processes for marketing and sales strategies. If you have specific columns or characteristics in your dataset, the implementation can be tailored further! Let me know if you have any questions or need more details!