Teaching

Neural Networks and Deep Learning

I am the coordinator for the “Neural Networks and Deep Learning” course at Université de Lorraine, in the Natural Language Processing (NLP) M2 program.

Course outline:

1. Introduction and Feedforward Neural Networks
2. Training Neural Networks
3. Advanced Training and Engineering
4. Convolutional Neural Networks
5. Recurrent Neural Networks
6. Attention and Visualization
7. Generative Models

Resources: lecture slides and practical notebooks.

I also teach practicals for the same course in the Cognitive Sciences M2 program.

Automatic Speech Recognition

From 2021 to 2024, I used to teach practicals for the “Speech Recognition and Synthesis” course (M2 NLP program). The corresponding notebooks are available here.