Mathematics AI Foundations & Optimization
Advanced mathematical optimization techniques for AI
About This Project
This project focuses on developing a large general-learning framework based on mathematical optimization principles. It demonstrates advanced feature extraction and dimensionality reduction techniques essential for building AI models from scratch to effectively train functions on vast datasets.
Core Concepts
- Mathematical optimization principles
- Linear algebra, calculus, probability
- Optimization algorithms (gradient descent, etc.)
- Dimensionality reduction techniques
- Advanced feature extraction
Key Knowledge/Skills
- Linear algebra, calculus, probability
- Optimization algorithms (multivariable)
- Algorithmic thinking and reasoning
- Mathematical proofs and derivations
Coursework Covered
Mathematics and Computational Foundations for AI