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UNIT-2
ADVANCED CONCEPTS OF
MODELING IN AI
Computer science has changed how we live, work, and use technology, leading to progress in areas like artificial
intelligence, data science, cybersecurity, and robotics. It helps solve difficult problems using smart programs, automation,
and data analysis. Before learning about modelling, let us first revise some of the basic terminologies of AI.
Revisiting AI, ML, DL
AI is a broad field that encompasses various technologies, including Machine Learning and Deep Learning.
These technologies are interconnected and can be understood as follows:
It is the ability of machines to simulate
Artificial Intelligence
human intelligence.
It is a subset of Artificial Intelligence that
Machine Learning enables machines to learn from data
and improve their performance without
explicit programming.
It is a subset of Machine Learning that
Deep Learning
uses neural networks to process large
amounts of data and solve complex
problems.
Let us understand AI, ML and DL in detail.
AI
Artificial Intelligence (AI) is a fast-growing technology that allows machines to do tasks that usually need human
intelligence, like learning, solving problems, and making decisions. It imitates some abilities of the human brain,
such as recognising patterns and understanding information, but it cannot fully match the brain’s complexity.
ML
ML stands for Machine Learning, which is a subset of Artificial Intelligence. It uses statistical methods to enable
machines to learn and improve from experience without being explicitly programmed. Machine Learning is one
of the most widely used techniques for building AI systems worldwide. It involves teaching machines to interpret,
process, and analyse data to solve problems effectively.
Advanced Concepts of Modeling in AI 113

