/EL_3003-IA_et_Deep_Learning

EL_3003-IA_et_Deep_Learning is an introduction to deep learning. The final project consists in comparing different types of classifiers such as CNN, KNN, SVM, on a face recognition problem.

Primary LanguageJupyter Notebook

EL_3003 Intelligence Artificiel et Deep Learning

EL 3019 Data Sciences is an academic course 🧑‍🎓

Warning : This is an ongoing project

Unit description :

The unit is an introdution to deep learning, with keras. We studied ConvNet and Dense neural netwoks. A focus is made on hyper-parameters, and regularisation techniques. The principal data proced are images from the MNIST dataset or some custom datasets.

Labs :

The first six labs are training exercises, each focusing on a specific part of the deep learning process.

Project :

The final project is to do face rocognition on a small data base with a CNN, and then compare the efficency with other kind of classifier, such as KNN, SVM, and so on.

Find here our report on the final project

Packages :
  • cv2
  • dlib
  • tensorflow / keras
  • numpy
  • mathplotlib
  • scikit-learn