Learning Materials

This page collects learning materials and technical notes. Some sections are placeholders for materials I plan to add later.

• Linear Algebra - vectors, matrices, decompositions, and tools for machine learning.
• Calculus - derivatives, gradients, optimization, and continuous mathematics.
• Machine Learning - learning algorithms, optimization, and implementation notes.
• Quantum Computing - quantum states, circuits, algorithms, and simulation.
• Quantum Machine Learning - quantum-assisted learning methods and QML research notes.
• Real Quantum Projects - project-based materials for learning quantum computing and quantum machine learning.