The term “machine learning” was coined by Arthur Samuel, a computer scientist at IBM and a pioneer in AI and computer gaming. Samuel designed a computer program for playing checkers. The more the program played, the more it learned from experience, using algorithms to make predictions.

Machine learning, like the human brain, relies on input, such as training data or knowledge graphs, to grasp entities, domains, and their connections. Deep learning can begin once entities have been defined.

Observations or data, such as examples, direct experience, or instruction, are used to start the machine learning process. It searches for patterns in data so that it can draw conclusions based on the examples presented. The basic goal of machine learning is to allow computers to learn without human intervention and change their activities accordingly.
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