AP-157-dump

Computational Analysis and Modeling in Physics

Currently taking this class under Ma'am May Lim, PhD and Sir Louie John Rubio.

Verbatim description: "Computational models in physics; numerical simulations of physical systems; stochastic simulation and algorithms; image processing; multidimensional detection techniques; pattern recognition"

Reference(s)

1. Kinzel, W., Reents, G., & Clajus, M. (1998). Physics by computer: programming physical problems using Mathematica and C (pp. I-VIII). Springer.
2. Downey, A. B. (2016). Think complexity (v. 2.6.3). Green Tea Press.
3. Coscia, M. (2021). The atlas for the aspiring network scientist. arXiv preprint arXiv:2101.00863.
4. Aase N. H., Sudbø A., Øyre, E. S., & Støvneng, J. A. (2019). Equilibrium monte carlo simulation of the 2D Ising model. Retrieved from https://nbviewer.org/urls/www.numfys.net/media/notebooks/Monte_Carlo_Ising.ipynb
5. Shlens, J. (2014). A tutorial on principal component analysis. arXiv preprint arXiv:1404.1100.
6. Madhavan, S. & Sturdevant, M. (2019, December 3). Learn regression algorithms using Python and scikit-learn. IBM Developer. Retrieved from https://developer.ibm.com/tutorials/learn-regression-algorithms-using-python-and-scikit-learn/
7. Madhavan, S. & Sturdevant, M. (2019, December 3). Learn classification algorithms using Python and scikit-learn. IBM Developer. Retrieved from https://developer.ibm.com/tutorials/learn-classification-algorithms-using-python-and-scikit-learn/