📊 Linear Regression

This project applies Linear Regression to predict placement outcomes using features from the placement.csv dataset available on Kaggle.

📁 Dataset

The dataset used in this project is sourced from Kaggle and contains information about student academic performance and placement outcomes.

• Features include: academic scores, work experience, specialization, etc.
• Target variable: salary or placement status.

🔧 Tools & Libraries

• Python 🐍
• Pandas & NumPy
• Matplotlib & Seaborn (for visualization)
• Scikit-Learn (for model training and evaluation)

📈 Project Workflow

1. Data Loading
   Load and explore the dataset.

2. Preprocessing

   • Handle missing values
   • Encode categorical variables
   • Split into training and test sets

3. Modeling

   • Apply Linear Regression
   • Evaluate using metrics like R², MAE, MSE

4. Visualization

   • Plot regression line
   • Visualize residuals and performance