This document explains artificial intelligence (AI) and its subset, machine learning (ML), which allows systems to learn and improve from experience without explicit programming. It defines ML as the scientific study of algorithms and models that utilize training data for making predictions or decisions. Additionally, it mentions various applications of ML, such as email filtering and computer vision.

1. MACHINE LEARNING
J.B.POO MAHA VINU SHREE

4. • Artificial intelligence (AI) is often used to describe
machines that mimic "cognitive" functions that humans
associate with the human mind, such as "learning" and
"problem solving".
• Machine learning is an application of
artificial intelligence (AI) that provides systems the ability
to automatically learn and improve from experience
without being explicitly programmed.
• Deep learning is a subset of machine learning in artificial

5. MACHINE LEARNING (ML)
• ML is the scientific study of algorithms and statistical models that
computer systems use to perform a specific task without using
explicit instructions, relying on patterns and inference instead.
• It is seen as a subset of artificial intelligence.
• ML algorithms build a mathematical model based on sample data,
known as "training data", in order to make predictions or decisions.
• ML algorithms are used in a wide variety of applications, such
as email filtering and computer vision, effectively performing the task.

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