Neural Networks & Deep Learning
📋 What it is
Neural networks are layers of simple math units, loosely inspired by brain cells, that learn complex patterns.
🗣️ Coach says
A neural network is built from many tiny math units ("neurons") connected in layers, loosely inspired by the brain. Each layer passes signals to the next, and by adjusting the connections during training, the network learns very complex patterns. "Deep" just means it has many layers.
🧠 Memory hook
Neural net = layers of tiny math units. Training adjusts the connections. "Deep" = many layers.
😂 Giggle
Why did the AI break up with the internet?
Too many toxic relationships in the training data!
😲 Whoa!
A large modern neural network can have hundreds of BILLIONS of adjustable connections — far more than there are stars in the Milky Way.
✅ Quick check: What does "deep" mean in "deep learning"?
Say your answer out loud first — then reveal.
That the neural network has MANY layers of units stacked up, letting it learn more complex patterns.
"Deep" refers to many layers in the network.
🧪 Try it! (2 minutes)
Stack your hands in "layers" and pass a squeeze from bottom to top — signals flowing through a network.