Student-focused study of the main deep learning methods and their
Basic models: Convlutional Neural Networks (CNN), stacked/denoising autoencoders,
Recurrent Neural Networks (including Long-Short-Term Memory Networks - LSTM).
Advanced models. Study of development frameworks for deep learning. Applications
of deep learning models for real-world problems.