This module is the third and final part of the "Neuron Networks and Deep Learning" certificate. The objective is to deploy a responsible solution based on deep learning, focusing on interpretability and social and ethical implications.
This course will give you :
An understanding of deep neural networks
Concrete experience with the deployment and hosting of an AI model
The tools to design responsible deep learning solutions that meet social and ethical challenges.
Day 1: Interpretability of artificial neural networks
How to understand and explain what happens in an artificial neural network? Modeling in the form of a “black box”.
The main concepts covered in this module are: interpretability, action plan and policy of a model, and the Python SHAP and LIME libraries.
Day 2: Deployment of a deep learning model
Concrete example of the deployment of a deep learning and focus model on a few specialized frameworks.
The main concepts covered in this module are: deployment, data science workload and Strealit and FastAPI frameworks.
Day 3: Responsible deployment of a deep learning model
Focus on the interpretability of a model and consideration of the social and ethical implications of deep learning.
The main concepts covered in this module are: deep learning models, interpretability, deployment.
TRAINERS / TEACHERS
Emmanuel R. Goffi
Expertise : AI Ethics
Associate Professor of AI Ethics and Director of International Relations | Director of the Ethics & IA Observatory - Sapiens Institute