nrtedesco

Deep Learning

Notes from CS 7643: Deep Learning at Georgia Tech.

Series

Chapters

20 chapters
  1. 01Linear Classifiers and Gradient DescentModule 1 of CS 7643 - Deep Learning @ Georgia Tech.
  2. 02Neural NetworksModule 2 of CS 7643 - Deep Learning @ Georgia Tech.
  3. 03Optimization of Deep Neural NetworksModule 3 of CS 7643 - Deep Learning @ Georgia Tech.
  4. 04Data Wrangling (Meta)Module 4 of CS 7643 - Deep Learning @ Georgia Tech.
  5. 05Convolutional and Pooling LayersModule 5 of CS 7643 - Deep Learning @ Georgia Tech.
  6. 06CNN Backprop + Common ArchitecturesModule 6 of CS 7643 - Deep Learning @ Georgia Tech.
  7. 07CNN VisualizationModule 7 of CS 7643 - Deep Learning @ Georgia Tech.
  8. 08Advanced Computer Vision ArchitecturesModule 8 of CS 7643 - Deep Learning @ Georgia Tech.
  9. 09Introduction to Structured RepresentationsModule 9 of CS 7643 - Deep Learning @ Georgia Tech.
  10. 10Language Modeling (Meta)Module 10 of CS 7643 - Deep Learning @ Georgia Tech.
  11. 11Neural Attention Models (Meta)Module 11 of CS 7643 - Deep Learning @ Georgia Tech.
  12. 12Machine Translation (Meta)Module 12 of CS 7643 - Deep Learning @ Georgia Tech.
  13. 13Generative ModelingModule 13 of CS 7643 - Deep Learning @ Georgia Tech.
  14. 14Denoising Diffusion Probabilistic ModelsSupplement to Module 13 of CS 7643 - Deep Learning @ Georgia Tech.
  15. 15Embeddings (Meta)Module 14 of CS 7643 - Deep Learning @ Georgia Tech.
  16. 16Scalable TrainingModule 15 of CS 7643 - Deep Learning @ Georgia Tech.
  17. 17Responsible AIModule 16 of CS 7643 - Deep Learning @ Georgia Tech.
  18. 18Reinforcement LearningModule 17 of CS 7643 - Deep Learning @ Georgia Tech.
  19. 19Unsupervised and Semi-Supervised LearningModule 18 of CS 7643 - Deep Learning @ Georgia Tech.
  20. 20Translation and ASR (Meta)Module 19 of CS 7643 - Deep Learning @ Georgia Tech.