Machine Learning algorithms are broadly classified into the following categories:
Trained using labeled data
Examples:
Linear Regression
Logistic Regression
Decision Tree
Random Forest
Support Vector Machine (SVM)
Trained using unlabeled data
Examples:
K-Means Clustering
Hierarchical Clustering
Apriori Algorithm
PCA
Use both labeled and unlabeled data
Example: Image classification with limited labels
Learn through rewards and penalties
Examples:
Q-Learning
Deep Q Network (DQN)
Policy Gradient
Supervised Learning → Uses labeled data
Unsupervised Learning → Finds hidden patterns
Reinforcement Learning → Learns by experience
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