Deep Learning

Now that we are comfortable in building and training a neural network with one hidden layer, we can look at more complex architecture with deep learning.

Deep learning is just an extension of traditional neural networks but with deeper and more complex architecture. Deep learning can model very complex patterns, be applied in tasks such as detecting objects in images and translating text into a different language.

Shallow versus Deep Networks

Now that we are comfortable in building and training a neural network with one hidden layer, we can look at more complex architecture with deep learning.

As mentioned earlier, we can add more hidden layers to a neural network. This will increase the number of parameters to be learned but can potentially help to model more complex patterns. This is what deep learning is about: increasing the depth of a neural network to tackle more complex problems.

For instance, we can add a second layer to the neural network we presented...