numerics-review

Jupyter notebooks with answers to the the end of chapter review questions for the textbook Scientific Computing by Michael Heath (Heath, 2018).

I compiled these notebooks while taking CS 450 Numerical Analysis at UIUC and they come without any guarantee of accuracy or endorsement by the textbook author.

I started a similar repository containing the algorithm pseudocode from the textbook implemented in numpy and scipy at marcoemorais/numerics-python.

If you find this repo helpful, please star this repository. Thank you!

@book{heath2018scientific,
  title={Scientific computing: an introductory survey},
  author={Heath, Michael T},
  volume={80},
  year={2018},
  publisher={SIAM}
}

Chapter Notes

Review-Table-of-Contents

Review-01-Scientific-Computing

Review-02-Systems-of-Linear-Equations

Review-03-Linear-Least-Squares

Review-04-Eigenvalue-Problems

Review-05-Nonlinear-Equations

Review-06-Optimization

Review-07-Interpolation

Review-08-Numerical-Integration-and-Differentiation

Review-09-Initial-Value-Problems-for-ODE

Review-10-Boundary-Value-Problems-for-ODE

Review-11-Partial-Differential-Equations

Review-12-Fast-Fourier-Transform

Review-13-Random-Numbers-and-Stochastic-Simulation

Study Guides

Final-Exam-Study-Guide