Hi everyone,
I’m excited to share a personal project I’ve been working on: a series of notebooks covering fundamental aspects of Deep Learning, from derivatives and gradient descent to Transformer architectures. My goal is to make these concepts more accessible to learners of all levels.
GitHub Repository: GitHub - SimonThomine/CoursDeepLearning: Un regroupement de notebooks pour apprendre le deep learning à partir de 0
Note: The course materials are currently in French.
About the Project
The course is still a work in progress, and I’m actively developing it during my spare time. Some parts draw inspiration from well-known English-language resources, such as Andrej Karpathy’s videos and DeepLearning.ai courses, as well as French resources.
How You Can Help
Feedback: I’d love to hear your thoughts and suggestions for improvement.
Spread the Word: Share the project with anyone who might find it useful.
Contributions: Feel free to contribute to the project if you’re interested.
Whether you’re just starting your Deep Learning journey or looking to deepen your understanding, I hope these notebooks can be a valuable resource.
Looking forward to your feedback and suggestions!