Artificial intelligence (AI) is a vast area of computer science that focuses on the development of systems that have the capacity to reason, learn, and act independently. AI research has had great success in creating efficient methods for addressing a variety of issues, from game play to medical diagnosis.
Machine learning (ML) is a branch of artificial intelligence that concentrates on creating methods that let computers learn from data without being explicitly programmed. Large datasets of labeled samples are used to train ML algorithms, which then learn to find links and patterns in the data that may be used to predict or decide.
The primary distinction between AI and ML is that, whereas ML is primarily concerned with creating algorithms that enable computers to learn from data, AI is more concerned with the construction of intelligent beings in general.
Here is a table that summarizes the key differences between AI and ML
| Feature | AI | ML |
| Definition | An extensive area of computer science concerned with the development of intelligent agents | A branch of artificial intelligence that focuses on creating algorithms that enable computers to learn from data |
| Goal | To create intelligent agents that can reason, learn, and act autonomously | To create algorithms that enable computers to understand data and anticipate or take actions |
| Methods | A number of approaches, including rule-based systems, expert systems, and machine learning | Algorithms for machine learning |
| Applications | A large number of uses, such as gaming, medical diagnostics, and financial trading | Applications for a range of things, such spam screening, product recommendations, and fraud detection |
