Machine learning is a subset of artificial intelligence that focuses on building systems that can learn from and make predictions or decisions based on data. Instead of being explicitly programmed to perform a task, machine learning algorithms use statistical techniques to identify patterns and relationships in data.
Key Concepts
- Types of Learning:
- Supervised Learning: The model is trained on labeled data, meaning the input comes with corresponding output labels (e.g., predicting house prices based on features like size and location).
- Unsupervised Learning: The model learns from unlabeled data, identifying patterns or groupings without pre-defined labels (e.g., clustering customers based on purchasing behavior).
- Reinforcement Learning: The model learns by interacting with an environment, receiving rewards or penalties for actions taken (e.g., training a robot to navigate a maze).
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