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  • Welcome to 7870

Part 1. Linear Algebra

  • A Deeper look at Vectors
  • Linear Algebra in Python with Numpy
  • Eigenvectors, Unitary Matrices, and Matrix Decompositions
  • Linear Regression and Least Squares

Part 2. Probability

  • Intro to Probability
  • Using Random Numbers in Numpy
  • Conditional Probability and Bayes Rule
  • Bayesian Inference
  • Monte Carlo
  • Markov Chain Monte Carlo
  • Detailed Balance and the Metropolis-Hastings Algorithm

Part 3. Numerical Differential Equations

  • Intro to Numerical Integration
  • More on Numerical ODEs
  • From ODE to PDE
  • Optimization
  • Nonlinear Regression
  • Automatic Differentiation and JaX
  • Repository
  • Open issue

Index

By Erik Thiede

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