This is my knowledge base.
Math
- Mathematical Analysis - foundation of advance topics: real number, limits, continuous function, series…
- Linear Algebra - tools for manipulating data efficiently.
- Statistics: tools for analyzing data and making decisions.
Lecture Notes
- Artificial Intelligence:
- Searching Algorithms(A star, CSP, Adversarial Search)
- Markov Decision Process
- Machine Learning Principles:
- Estimation
- Parameter Estimation(MLE, MAP)
- Non-Parametric Estimation(KDE)
- Optimization Methods(EM, Lagrange Multiplier)
- Decisioning
- Bayesian Decision Theory
- Estimation
- Computer Graphics:
- Object Modeling
- Rendering Pipeline
- Ray-Tracing
- Aliasing and Anti-Aliasing
- Natural Language Processing:
- Language Modeling
- Word Embeddings
- Transformers