# Neural Networks
- Components
- Synaptic weights $w_i$
- Bias
- Summing function
- Activation function
- Logistic
- Sigmoid
- Hyperbolic tangent
- Gradient descent
- Layers: input, hidden, and output
- Deep neural networks
- Advantages
- Multimodal data
- Closely approximate any function, given enough neurons and training data
- Disadvantages
- High cost
- Large dataset required
- Local optima
- Hart to interpret