Machine Learning
AI is technology that enables computers and machines to simulate human learning.
What is Machine Learning?
Machine Learning (ML) is a branch of Artificial Intelligence (AI) that allows computers to learn from data and improve their performance.
Instead of writing step-by-step instructions, we feed the computer with data + examples, and the system finds patterns and makes predictions/decisions on its own. Just like humans learn from practice, a computer learns from data.
Key Idea
👉 Traditional Programming:
Programmer writes rules ➝ Computer follows rules ➝ Produces output.
👉 Machine Learning:
Programmer provides data & examples ➝ Computer learns patterns ➝ Creates its own rules ➝ Produces output.
👉 Without ML:
To recognize spam emails, you’d hard-code rules like “if subject has ‘lottery’ ➝ mark as spam.”
👉 With ML:
You give the system thousands of examples of spam and not spam. The system learns the difference and then predicts whether a new email is spam.
Types of Machine Learning
- Supervised Learning
- Learn from labeled data (input + correct output given).
- Example: Predicting house prices based on features (size, location, rooms).
- Unsupervised Learning
- Learn from unlabeled data (no predefined answers).
- Example: Grouping customers into clusters based on buying habits.
- Reinforcement Learning
- Learn by trial and error, getting rewards or penalties.
- Example: Training a robot to walk or an AI to play chess.
Real-Life Applications
- 🎥 Netflix/YouTube recommendations
- 🚗 Self-driving cars
- 🎙️ Voice recognition (Alexa, Siri)
- 💳 Fraud detection in banks
- 🏥 Medical image analysis