1. Introduction
Artificial Intelligence (AI): Simulation of human intelligence in machines to perform tasks like
problem-solving, decision-making, and learning.
Machine Learning (ML): A subset of AI where machines improve performance through data and
experience without explicit programming.
2. Key Differences Between AI and ML
AI: Broader concept encompassing intelligent systems (e.g., robotics, NLP).
ML: Focuses on algorithms enabling machines to learn patterns.
AI uses ML as one of its tools to achieve intelligence.
3. Types of AI
Narrow AI: Focused on specific tasks (e.g., Siri, recommendation systems).
General AI: Hypothetical, capable of performing any intellectual task.
Super AI: Theoretical stage where machines surpass human intelligence.
4. Types of Machine Learning
1. Supervised Learning:
Trains on labeled data.
