How Do Machines Learn?
A simple roadmap of all learning methods in Machine Learning (ML) Think of a robot trying to become smarter. There are only a few basic ways we can teach it: 1. Supervised Learning You show the machine examples and give it the answers. It learns by comparing its guesses to the correct answers and adjusting. Example: You show it 100 photos of cats and dogs labeled as “cat” or “dog”. It learns to tell them apart. We'll dive into this next! 2. Unsupervised Learning You give it data, but no answers. It tries to find patterns or group similar things. Example: You give it 1,000 customer reviews with no ratings. It learns to group similar ones together (like “angry” vs. “happy”). 3. Reinforcement Learning (RL) You give it a goal, and it learns by trial and error. It gets rewarded or punished and learns what works. Example: A robot in a maze learns the right path by getting points for moving closer to the exit. 4. Self-Supervised Learning It creates...