What subset of artificial intelligence involves algorithms that learn from data?

Machine learning is a subset of artificial intelligence that focuses on the development of algorithms that allow computers to learn from and make predictions based on data. The key aspect of machine learning is its ability to improve performance on a specific task as it is exposed to more data over time, without being explicitly programmed for each task.

In machine learning, various algorithms are employed to identify patterns, make decisions, and derive insights from the input data. This process involves training a model on a dataset, which allows the model to generalize and make accurate predictions on new, unseen data. The essence of machine learning lies in its adaptive and self-improving nature, which distinguishes it from traditional programming approaches where explicit rules and logic are in place.

Other options, while related, refer to more specific domains or techniques within the broader machine learning space. Data analysis, for instance, encompasses a wider array of techniques to inspect, cleanse, transform, and model data to discover useful information but does not inherently involve learning algorithms. Neural networks are a specific architecture used to implement machine learning models, particularly those that deal with complex data patterns, while deep learning, a further specialization of neural networks, involves extremely deep networks that can capture high-level abstractions in data. However, both neural networks