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Artificial Intelligence (AI) and machine learning (ML) are related concepts but have distinct meanings.
Artificial Intelligence:
Artificial Intelligence refers to the broader field of creating intelligent machines or systems that can perform tasks that typically require human intelligence. AI involves developing algorithms and systems that can perceive their environment, reason, learn, and make decisions. It aims to replicate or simulate human intelligence in machines.
Machine Learning:
Machine Learning is a subset or application of AI. It involves developing algorithms that allow computers to learn and improve from data without being explicitly programmed. Instead of being explicitly programmed for specific tasks, machine learning algorithms learn from patterns and examples in the data. They automatically identify and learn from patterns, make predictions, or take actions based on the data they are trained on.
In simpler terms, AI is the broader concept that encompasses the idea of creating intelligent machines, while machine learning is a specific approach or technique within AI that focuses on enabling machines to learn from data and improve their performance over time.
To summarize:
AI is the overarching field that aims to develop intelligent machines. Machine learning is a subset of AI that focuses on algorithms and techniques that allow machines to learn from data and improve their performance. Machine learning is one of the ways AI systems can be created, but there are also other approaches like rule-based systems, expert systems, and deep learning, which is a subfield of machine learning.