Machine learning is a subset of artificial intelligence (AI) that involves the development of algorithms and statistical models that enable computers to learn from and make decisions or predictions based on data, without being explicitly programmed to do so.
In machine learning, algorithms iteratively learn from data, allowing computers to find hidden insights and patterns without being explicitly programmed where to look. This learning process involves the algorithms improving their performance on a task as they are exposed to more data over time.
There are several types of machine learning, including supervised learning, unsupervised learning, and reinforcement learning, each with its own techniques and applications. Supervised learning involves training a model on a labeled dataset, where the algorithm learns to map input data to the correct output. Unsupervised learning involves training on unlabeled data to learn patterns and structures within the data. Reinforcement learning involves training an algorithm to make sequences of decisions by rewarding or penalizing the algorithm based on its actions.
