PRINCIPLE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

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Published Date: 2024-08-29
Author Name: Ms. Pakiza Khan Ms. Rekha Yadav Ms. Nidhi Pare Kashiv Prof. Shivangi

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The principles of artificial intelligence (AI) and machine learning (ML) are foundational to developing systems that emulate human-like intelligence and improve over time through data-driven learning. AI aims to create machines capable of tasks such as reasoning, problem-solving, and decision-making by simulating cognitive processes. ML, a core component of AI, focuses on designing algorithms that enable computers to learn from and make predictions based on large datasets. Central to these principles are the concepts of data-driven learning, where models are trained on data to identify patterns and make informed predictions; generalization, which ensures models can apply learned knowledge to new, unseen data; and addressing ethical concerns such as bias to ensure fair and transparent outcomes. Together, these principles drive the advancement of intelligent systems that enhance decision-making, efficiency, and innovation across diverse applications.