✅ Must-Know Machine Learning Algorithms 🤖📊

🔵 Supervised Learning
📍 Classification:
⦁ Naïve Bayes
⦁ Logistic Regression
⦁ K-Nearest Neighbor (KNN)
⦁ Random Forest
⦁ Support Vector Machine (SVM)
⦁ Decision Tree

📍 Regression:
⦁ Simple Linear Regression
⦁ Multivariate Regression
⦁ Lasso Regression

🟡 Unsupervised Learning
📍 Clustering:
⦁ K-Means
⦁ DBSCAN
⦁ PCA (Principal Component Analysis)
⦁ ICA (Independent Component Analysis)

📍 Association:
⦁ Frequent Pattern Growth
⦁ Apriori Algorithm

📍 Anomaly Detection:
⦁ Z-score Algorithm
⦁ Isolation Forest

⚪ Semi-Supervised Learning
⦁ Self-Training
⦁ Co-Training

🔴 Reinforcement Learning
📍 Model-Free:
⦁ Policy Optimization
⦁ Q-Learning

📍 Model-Based:
⦁ Learn the Model
⦁ Given the Model

💡 Pro Tip: Master at least one algorithm from each category. Understand use cases, tune parameters & evaluate models.

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