Machine learning is a subfield of artificial intelligence that enables systems to learn from data without being explicitly programmed. It's about giving computers the ability to improve their performance on a specific task over time, based on experience.
Key Concepts
Here's a breakdown of some core concepts:
- Supervised Learning: Training algorithms with labeled data to predict outcomes. (e.g., predicting house prices based on features).
- Unsupervised Learning: Discovering patterns and insights in unlabeled data. (e.g., customer segmentation).
- Reinforcement Learning: Training agents to make decisions in an environment to maximize a reward. (e.g., training a robot to walk).
- Algorithms: Common algorithms include Linear Regression, Logistic Regression, Decision Trees, Support Vector Machines, and Neural Networks.
Applications
Machine learning is transforming industries across the board:
- Healthcare: Disease diagnosis, drug discovery.
- Finance: Fraud detection, algorithmic trading.
- Marketing: Personalized recommendations, targeted advertising.
- Autonomous Vehicles: Self-driving cars rely heavily on machine learning.