Machine Learning (ML) is a branch of artificial intelligence (AI) that enables computer systems to learn from data and improve performance over time without being explicitly programmed. Instead of following fixed rules, ML models use algorithms to analyze patterns, make predictions, and automate decision-making.
Key Types of Machine Learning:
-Supervised Learning: Uses labeled data to train models (e.g., predicting credit scores).
-Unsupervised Learning: Finds hidden patterns in unlabeled data (e.g., customer segmentation).
-Reinforcement Learning: Learns through trial and error using feedback or rewards (e.g., robotics, game AI).
Applications:
-Customer Experience: Personalized recommendations and chatbots.
-Finance: Fraud detection and risk analysis.
-Healthcare: Predictive diagnostics and treatment planning.
-Marketing: Audience targeting and campaign optimization.
-Automation: Enhancing operational efficiency across industries.
Example:
An e-commerce site recommending products based on your browsing history is powered by machine learning algorithms.
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