Get an introduction to deep neural networks, their history and reasons for their popularity in the fields of natural language processing and image recognition.
2. Mathematical Foundations
Learn the basic mathematical foundations required for deep neural networks including problem representation via tensors, tensor operations and gradient descent.
3. Case Studies
Work on a case study based on IMDB ratings and see all required building blocks in action.