Machine Learning (ML) is a subset of Artificial Intelligence (AI) focused on the development of algorithms and statistical models that enable computers to perform a task without explicit instructions. Instead, these systems learn and make decisions based on patterns and inferences from data.

Definition of Machine Learning:

  • Machine Learning involves feeding large amounts of data into algorithms that allow the computer system to learn from and make predictions or decisions based on that data.
  • It’s a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look.

Relation with AI:

  • AI is the broader concept of machines being able to carry out tasks in a way that we would consider “smart.” It’s about creating machines that can simulate human intelligence processes.
  • Machine Learning is an application or a subset of AI. It’s essentially the current state-of-the-art in AI, where the focus is on the development of computer programs that can access data and use it to learn for themselves.
  • While AI encompasses a broad range of intelligent behaviors, ML is specifically concerned with the development of algorithms that can change their output based on data they consume, effectively learning from it.

In summary, while all machine learning is AI, not all AI is machine learning. Machine learning is a means by which we achieve AI, focusing on the development of systems that can learn from and make decisions based on data.

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