To build an artificial learning algorithm, start with the human brain.
A refresher on vectors, matrices, and optimization.
The building block of many neural networks.
Stringing it all together.
Using a model's outputs to train it to do even better.
Models to capture structural information within data.
Models to process sequential data by remembering what we already know.
A look into stochastic ANNs, adversarial techniques, vectorization, and other advanced topics.