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Deep Learning Course

Ressources for Deep Learning Course (VSE).

Grade breakdown:

  • Kaggle challenges: 30% of the total grade
    • Deadline on the 15th of March 2023, 5pm
    • Fitting functions (1D-1D & 5D-5D)
    • Binary face classification (with glasses or without glasses)
    • Multi (10) classes classification
    • Transfer Learning
  • Group Project: 70% of the grade
    • 2-3 per group
    • Deadline on the 2nd of April 2023, 11:59 pm
    • Must demonstrate understanding of deep learning & ability to lead a project
    • Easiest projects that are thoroughly understood are preferred to complicated projects that are only scratched the surface
    • Slides and written report must be in English. Presentation doesn't need to.

Projects Ideas

"Mathy" projects:

  • deep to shallow: deep (>2 hidden layers) to shallow (1 hidden layer) network
  • perturb weights of a network to assess which neurons are the most “sensitives” (maybe compare wide and deep?)

CNN projects:

  • follow up on digits classification: hand written characters classification
  • measure how far two handwritings are from images samples (use siamese networks to create a distance)
  • follow up on TD8: from medical decathlon (http://medicaldecathlon.com/), try to segment other organs (we will do prostate and hippocampus in TD8 & TD8bis)
  • realistic person not existing: this website generates artificial images of people some are more realistic than others; create a network that discriminate realistic from unrealistic ones

RNN projects:

  • predict the language spoken from some audio record
  • predict the area of math to which belong the latex formula

GAN projects:

  • conditional gans on pokemons: generate intermediate frames for the evolution of pokemons (this could be a beginning: https://becominghuman.ai/generating-new-pokemons-using-gans-ceba1c6dc676)
  • mixing faces: take images of faces and create a mixture of them, you can then create the "average face" of your group, your family, etc...
  • how will our babies look like: take two face images and generate a younger version of the mixed faces

NLP projects:

  • autocomplete based on previous messages of the conversation
  • automatic texting in a conversation (similar to the above, but more ambitious... How long can you hold before the other person finds out? this is called the Turing test)
  • automatic group conversation image generation based on conversation title/messages

Drive folder with datasets:

https://drive.google.com/drive/folders/1_KqzmBVvZKwvLi0a1W3P6wPa-IgwnmLP?usp=share_link

Colab notebook example that mounts your drive:

https://colab.research.google.com/drive/1Ummw01RU9TeSnmoUIBAPR88wfTpLvZUD?usp=sharing

Kaggle links:


Course ressources from last year: https://m2dsupsdlclass.github.io/lectures-labs/

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Ressources for Deep Learning Course (VSE).

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