Machine Learning (ML)
Machine Learning is a subset of AI that focuses on the development of algorithms which allow computers to learn patterns and make decisions from data rather than following strictly pre-programmed rules. In ML, the emphasis is on training models with historical data so that they can make accurate predictions or classifications when exposed to new, unseen data.
Types of Machine Learning:
- Supervised Learning: Involves training a model on a labeled dataset, where each example comes with a known output. This is commonly used for tasks like classification (e.g., spam detection) and regression (e.g., predicting house prices).
- Unsupervised Learning: Deals with unlabeled data, aiming to discover underlying structures or patterns, such as clusters in data points (e.g., customer segmentation).
- Reinforcement Learning: In this approach, an agent learns to make decisions by interacting with an environment and receiving feedback in the form of rewards or penalties, leading to the development of effective strategies over time.