Lecture Notes

This page contains a list of links to PHY151 lecture notes.

• Lecture 1: Numerical Methods: Integration and ODE&PDEs
• Lecture 2: Intro to Statistics
• Lecture 3: More Statistics and Intro to Data Modeling
• Lecture 4: Linear Algebra
• Lecture 5: Information Theory, Entropy, Experiment Design
• Lecture 6: Nonlinear Equations and Optimization
• Lecture 7: Monte Carlo Sampling and Integration
• Lecture 8: Advanced Bayesian Concepts (Probabilistic graphical models, Hierarchical Bayesian models, etc)
• Lecture 9: Distributional Approximations
• Lecture 10: Best Practices of Statistical Analysis
• Lecture 11: From Interpolation to Regressions to Gaussian Processes
• Lecture 12: Fourier Methods
• Lecture 13: Classification
• Lecture 14: Neural Networks, Deep Networks, Convolutional Nets, etc

A full list can be found at on github