Class 6: How Machines Learn – Introduction to Machine Learning
Learning Objectives:
- Understand the machine learning process
- Learn about data, datasets, and training
- Recognize patterns in data
- Identify different types of machine learning
- Machine learning definition: “Computers learning from examples without being programmed for each specific task”
- The machine learning cycle: Data → Training → Testing → Prediction
- Supervised learning: Learning from labeled examples (like a teacher showing correct answers)
- Unsupervised learning: Finding patterns without labels
- Training data vs. test data
- Importance of diverse, quality data
Activities:
- Google Teachable Machine project: Training a model to recognize objects
- Thumbs-up/thumbs-down classification activity
- Cat vs. Dog classifier hands-on exercise
- Prediction matching game