🧠 Supervised Learning

Supervised learning is the core of modern machine learning — where models are trained to predict known outcomes based on labeled data.

This section focuses on:

• ✅ Building and training models like Logistic Regression, Decision Trees, Random Forests, and SVMs
  
• 📈 Evaluating model performance using accuracy, ROC curves, and AUC scores
  
• 🔄 Improving predictions with cross-validation and hyperparameter tuning
  
• 🔍 Understanding model predictions through visual explanations

💡 Supervised learning teaches your model what to look for — by learning patterns from labeled examples.

Whether you’re working on classification (e.g., predicting survival) or regression (e.g., predicting house prices), these methods will help you turn data into insight — and build models that generalize to the real world.