Course prepared for Sofia University: Palo Alto facility, 2024.
- (2024-03-31) Starting 2024 Spring Session
| N | Lecture | Desctription |
|---|---|---|
| 01 | Introduction | Introduction. Course logistics and syllabus. Deep Learning and Neural Nets. AI vs ML vs DL. DL History |
| 02 | GenAI | Generative AI: GAN, Diffusion |
| 03 | Transformers | Transformers: BERT, GPT, LLM, ChatGPT and Hallucinations |
| 04 | CV and ASR | Deep Learning Applications: Computer Vision, its Main Tasks (Classification, Detection, Segmentation, Image Enhancement) and Architectures (CNN and Transformer), Automatic Speech Recognition and its History (HMM) |
| 06 | Learning Frameworks | Learning Frameworks: Meta-Learning, Few-Shot Learning, Multi-Tasking, and Multi-Modality |
| 07 | Robustness | ML Robustness. Digital and Real-World Adversarial Attacks. Taxonomy of Adversarial Examples. l-norms |
| 08 | Autonomous Driving | Embodied AI. Automation levels. History of Autonomous Driving. Self-Driving and its Stack |
| 09 | Interpretability and Explainability | Interpretability of ML models. Explainability as a concept. Bias and Fairness in AI. AI Ethics |
| 10 | Exam | Final Exam: information and logistics. Design topics. Concepts topics |
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent