First Model Project

This project demonstrates the process of building and comparing simple machine learning models using Python and scikit-learn.

Project Overview

• Developed a basic machine learning project using Python and scikit-learn.
• Loaded and prepared a dataset for model training and testing.
• Split the data into features (X) and target (y) variables.
• Trained two models:
  • Linear Regression
  • Random Forest Regressor
• Compared both models based on prediction accuracy and performance metrics.
• Visualized results using matplotlib to compare predicted vs. actual values.

Things learned

• Data preprocessing and splitting
• Model training and evaluation
• Performance comparison
• Data visualization

Tools & Libraries Used

• Python
• scikit-learn
• NumPy
• matplotlib
• Google Colab