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Machine Learning involves teaching computers to learn from examples, mirroring human learning processes. It is a subset of Artificial Intelligence, and encompasses various real-world applications like video recommendations and facial recognition. The chapter guides readers through an introductory understanding of machine learning, its working mechanism, and provides a simple implementation using Python.
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References
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Final Test
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Term: Machine Learning
Definition: A field of artificial intelligence that focuses on enabling computers to learn from and make predictions based on data.
Term: Artificial Intelligence (AI)
Definition: The broader concept where machines perform tasks that typically require human intelligence.
Term: Deep Learning
Definition: A specialized subset of machine learning that utilizes neural networks to simulate human brain functioning.
Term: Model
Definition: The representation that learns from examples in machine learning.
Term: Prediction
Definition: The outcome forecasted by the model based on input data.
Term: Training
Definition: The process of teaching a model using training data.
Term: Input
Definition: The data or examples provided to the model to make predictions.
Term: Output
Definition: The result or prediction generated by the model after processing input.