Introduction to AI/ML
What is Artificial Intelligence (AI)?
Artificial Intelligence (AI) is the field of computer science focused on creating systems capable of performing tasks that normally require human intelligence.
These tasks include reasoning, learning, problem-solving, perception, and language understanding.
Examples:
- Virtual assistants (Siri, Alexa)
- Recommendation systems (Netflix, YouTube)
- Self-driving cars
What is Machine Learning (ML)?
Machine Learning (ML) is a subset of AI that enables systems to learn from data and improve over time without being explicitly programmed.
Key concepts:
- Supervised Learning: Learn from labeled data (e.g., predicting house prices).
- Unsupervised Learning: Find patterns in unlabeled data (e.g., customer segmentation).
- Reinforcement Learning: Learn by interacting with the environment (e.g., training robots or game-playing AI).
Why AI/ML is Important
- Automates repetitive tasks and improves efficiency
- Provides insights from large datasets
- Powers modern technology across industries
Example Applications
- Healthcare: Predicting diseases from medical records
- Finance: Fraud detection and credit scoring
- Retail: Personalized recommendations
- Transportation: Optimizing routes and autonomous vehicles
Summary
AI is the broader concept of machines mimicking human intelligence, while ML is a way to achieve it through data-driven learning.
This course/book will guide you through the fundamental concepts, algorithms, and practical implementations of AI and ML.