Intro

Intro

Welcome to my knowledge bank, the place where you will find scrambling class notes and spaghetti codes.

Feel free to navigate through~

Content

• Machine Learning Theory
  • Gentle Start
  • Empirical Risk Minimization
  • PAC Learning
  • Bias-Complexity Tradeoff
  • VC-Dimension
  • Conclusion
• Machine Learning Algorithms
  • Intro
  • Linear Predictors
  • Boosting
  • Neural Networks
• Reinforcement Learning
  • Overview
  • Multi-armed Bandits
  • Markov Decision Process
  • Dynamic Programming
  • Monte Carlo Method
  • Temporal-Difference Learning
  • n-step Bootstrapping
  • Concurrent Q-Learning
  • Proximal Policy Optimization
• Optimization
  • Basics
  • 1D Search Methods
  • Gradient Descent
  • Conjugate Direction Methods
  • Newton's Method
  • Linear Programming
  • The Simplex Algorithm
  • Duality
  • Nonlinear Constrained Optimization - Equality
  • KKT
  • Lagrangian Duality
  • Convex Optimization
• Code
  • RL DP Code
  • Gradiant Descent Code
  • Linear Programming Code
  • 2048 Verilog
• Communication Protocols
  • Serial Communication
  • I2C
  • SPI
• Handwritten Notes