Where Deep Learning Wins (and Where It Doesn't)
Vision, language, audio — and when a simpler model is better.
Not Always the Answer
Deep learning is powerful, but it is not a magic hammer for every problem. Knowing when to reach for it is a real skill. 🎯
It Loves Vision
Deep nets dominate vision: classifying photos, detecting objects, and reading handwriting. Raw pixels are exactly the messy data they thrive on.
All lessons in this course
- AI vs Machine Learning vs Deep Learning
- Why Neural Nets Beat Hand-Crafted Features
- Where Deep Learning Wins (and Where It Doesn't)
- The Training Loop in Plain English