Summary of lecture CS224R (2025) Lecture 11. Model-Based RL
Summary of lecture CS224R (2025) Lecture 9. RL for LLMs:Preference Optimization
Summary of lecture CS224R (2025) Lecture 8. Reward Learning
Summary of lecture CS224R (2025) Lecture 7. Offline RL
Summary of lecture CS330 (2022) Lecture 6. Non Parametric Few-Shot Learning
Summary of lecture CS224R (2025) Lecture 6. Q-Learning
Summary of lecture CS330 (2022) Lecture 5. Optimization-Based Meta-Learning
Summary of lecture CS224R (2025) Lecture 5. Off-Policy Actor-Critic Methods
Summary of lecture CS330 (2022) Lecture 4. Black-Box Meta-Learning & In-Context Learning
Summary of lecture CS224R (2025) Lecture 4. Actor-Critic Methods
Summary of lecture CS330 (2022) Lecture 3. Transfer learning & Fine-tuning
Summary of lecture CS330 (2022) Lecture 2. Multi-task learning
Reflections on 2025 - Achievements, Regrets, and Resolutions
My experience using ChatGPT and Gemini Code Assist (Agent Mode)
Applying Taylor Expansion in various functions.
