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Machine Learning – Supervised & Unsupervised Algorithms — Guided Predictions vs. Pattern Discovery
9 min readJul 24, 2025
Topic Covered:
Supervised Learning: Guided Predictions
Linear Regression
Logistic Regression
Ridge & Lasso Regression
Decision Tree (Ensembles): Random Forest (Bagging), Gradient Boosting,, XGBoost (Boosting), Adaptive Boosting
Naive BayesUnsupervised Learning Algorithms: Pattern Discovery
Clustering: K-mean, K-nearest, DBSCAN, Heirarical
Dimesntion Reduction: Principal Component Analysis, Linear Discriminant Analysis
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Supervised Learning Algorithms
- You train the model with labeled data (input + correct output).
- You teach the model using examples that already have answers (called labels).
- It learns from these examples to predict the answers for new, unseen data.
You have labeled data
You want to make predictions
Linear Regression
- Predicts a continuous value.
- Example: Predict house price based on size, location.
