This repository contains notebook codes for the "Deep Learning" course, taught by Professors Galasso and Marini as part of the Bachelor of Science in Applied Computer Science and Artificial Intelligence at Sapienza Università di Roma.
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📅 Lecture Schedule:
- Tuesdays: 13:00 – 15:00 at Aula 103, Regina Elena Building D.
- Thursdays: 13:00 – 16:00 at Aula 11, Via Scarpa, Engineering Department.
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🧪 Exam Structure:
- A written exam covering topics and exercises discussed throughout the lectures.
- 📌 For official communications and course materials, please refer to the Google Site and Google Group pages of the course.
- 🛰 For additional references about the notebooks, consult the official website of the Dive into Deep Learning textbook.
- 📩 For any questions or clarifications, feel free to contact me directly.
9 October: Recap of mutilayer perceptrons and introduction to convolutional neural networks (Chapter 7.2)
23 October: Implementing AlexNet (Chapter 8.1)
25 November: Recap of sequence models (Chapters 9.1 and 9.2) and implementing models such as recurrent neural networks (Chapter 9.5), long short-term memory models (Chapters 10.1 and 10.5) and encoder-decoder models (Chapter 10.6 and 10.7)
27 November: Recap of multi-head attention and self-attention (Chapters 11.5 and 11.6) and implementing transformers (Chapter 11.7)