Machine learning के तीन मुख्य प्रकार हैं — supervised learning (labeled examples से सीखना), unsupervised learning (unlabeled data में patterns खोजना), और reinforcement learning (trial और reward के माध्यम से सीखना)। इन्हें समझना स्पष्ट करता है कि ML विभिन्न समस्याओं तक कैसे पहुँचता है।
The three main types
text
SUPERVISED LEARNING → learn from LABELED data (input → known correct output):
→ trained on examples with answers → learns to predict outputs for new inputs
→ for: classification (categorize), regression (predict numbers)
→ e.g. spam detection (labeled spam/not-spam), price prediction
UNSUPERVISED LEARNING → find patterns in UNLABELED data (no given answers):
→ discovers structure/groupings on its own
→ for: clustering (group similar items), dimensionality reduction, anomaly detection
→ e.g. customer segmentation, finding patterns
REINFORCEMENT LEARNING → learn through TRIAL and ERROR with REWARDS:
→ an agent takes actions, gets rewards/penalties, learns to maximize reward over time
→ for: game playing, robotics, control, decision-making