Neural Networks and Deep Learning

This course (6 CFUs) includes two modules of 3 CFUs each: the first module focuses on the theoretical foundations of neural networks and deep learning, while the second module covers more practical and implementation issues.

*** The first lecture is scheduled on January 14, 2020 at 9:00, Grey Room, TeCIP Institute.

Course Program

Course slides (Giorgio Buttazzo)

  1. Introduction to neural computing
  2. Hopfield networks
  3. Competitive learning
  4. Reinforcement learning
  5. Supervised learning
  6. Towards Deep Neural Networks (DNNs)
  7. DNN models
  8. Convolutional Neural Networks
  9. DNNs for object classification
  10. DNNs for object detection
  11. Recurrent Neural Networks
  12. Generative Adversarial Networks
  13. Applications of DNNs
  14. Frameworks for developing DNNs
  15. Implementing DNNs on GPGPUs