🎓 Artificial Intelligence student with a strong mathematical foundation and a deep interest in algorithms, computation, and theoretical aspects of AI.
I focus on understanding AI systems from first principles, rather than treating them as black-box tools.
- 🤖 Artificial Intelligence with emphasis on algorithmic reasoning
- 📐 Strong interest in mathematical structures behind computation
- 🧩 Enjoy formal problem solving and abstraction
-
Algorithms & Data Structures
Time complexity, space trade-offs, recursion, graph algorithms, and optimization strategies -
Mathematical Foundations of AI
Linear Algebra, Probability Theory, Discrete Mathematics, and their role in learning algorithms -
Machine Learning (from theory to practice)
Loss functions, optimization methods, generalization, and model behavior
- Languages: Python, Java
- Concepts:
- Algorithmic complexity analysis (Big-O, amortized analysis)
- Optimization methods (gradient-based reasoning)
- Problem modeling and abstraction
- Mathematical intuition behind learning algorithms
- Algorithm design patterns and correctness reasoning
- Bridging theoretical understanding with practical implementation
I believe strong AI systems are built on mathematical clarity, algorithmic efficiency, and rigorous reasoning, not just frameworks or APIs.
📫 GitHub: @Jason421412
📫 Email: jason421412@gmail.com
⚡ Fun fact: I care more about why an algorithm works than how fast I can code it.