Instructor: Xuemei Chen, xchen@nmsu.edu
Lecture: TR 9 - 10:15 @SH114 @zoom
office hours: T 10:15 - 11:15, R 11:30 - 12:30 @SH230 T 10:30 - 11:30, R 1:30 - 2:30 @zoom
I do tend to be on campus more on Tuesdays, Wednesdays, and Thursdays. But feel free to make appointment with me on any day.
This will be the main course website. Canvas is for grades recording, homework submission, and possible announcements.
I will post lecture notes and keep updating it.
For people who don't have Python or Jupyter notebook, a very easy solution is to download Anaconda (Python 3.7 version).
For people who already have Python but need to install Jupyter notebook, you may still install Anaconda as instructed previously, or install Jupyter notebook following https://jupyter.org/install.html.
The information above is some highlights of our Syllabus.
Please get a GitHub account if you don't have one yet. Email me your GitHub username.Once you have installed Jupyte Notebook, you can launch it using Anaconda, or you can simply execute "jupyter notebook" in the command line. Here is a tutorial that I found online.
For regular written exercises, you can either scan your work or type up your work (I don't prefer one way or another). In either case, you need to upload ONE SINGLE pdf on Canvas.
If you don't want to scan, you can turn in a physical copy of your work in class of the same day.
For python exercises, you will do your work in jupyter notebook following the format here. When you are done, print out a pdf. You need to submit TWO files to Canvas: the .ipynb file and the pdf printout.
| Date | Content | Assignment | Remarks | ||
|---|---|---|---|---|---|
| 1 | R | 1/23 | Introduction, binary, floating point representation | ||
| 2 | T | 1/28 | binary, rounding, machine epsilon | Getting started with Jupyter notebook | |
| 3 | R | 1/30 | addition, IEEE standard, scientific computing | HW1:Ch1:1-11, read this notebook | |
| 4 | T | 2/4 | nested poly, bisection | ||
| 5 | R | 2/6 | jupyter notebook, Newton's method | HW2:Ch1(13-15),Ch2(1-2); practice the tutorial notebook | HW1 due |
| 6 | T | 2/11 | secant method, jupyter notebook | practice the tutorial notebook | Quiz 1 |
| 7 | R | 2/13 | Matrix, vector, Matrix multiplication | HW3: Ch2(3-10), Ch3(1-3) | HW2 due |
| 8 | T | 2/18 | Gaussian elimination | ||
| 9 | R | 2/20 | LU | HW4:Ch3(4-14) | HW3 due |
| 10 | T | 2/25 | partial pivoting | Quiz 3 | |
| 11 | R | 2/27 | PLU | HW5: Ch3(15-22) | HW4 due |
| 12 | T | 3/3 | matrix in python, interpolation | HW6: Ch3(23-27). This matrix notebook is helpful. | |
| 13 | R | 3/5 | mid review, Lagrange Interp | See Canvas Announcement about midterm | Quiz 4, HW5 due |
| 14 | T | 3/10 | Newton Interp, Runge effect | Read this polynomial notebook | HW6 due |
| 15 | R | 3/12 | MIDTERM | ||
| Break | |||||
| 16 | T | 3/31 | logistics for online course | Practice this polynomial notebook | |
| 17 | R | 4/2 | chebyshev, spline | HW7: Ch4(1-10) | |
| 18 | T | 4/7 | cubic spline | ||
| 19 | R | 4/9 | python, trapezoidal rule | HW8: Ch4(13-19) | trial quiz, HW7 due |
| 20 | T | 4/14 | Simpson's rule | Quiz 7 | |
| 21 | R | 4/16 | composite quadrature, Gaussian quadrature | HW9: Ch4(11-12), Ch5(1-8) | HW8 due on 4/19 |
| 22 | T | 4/21 | HW8, Gaussian quadrature, some LA review | read 7.2.3, 7.2.4 of notes | |
| 23 | R | 4/23 | span, eigenvalue, PD | HW10: Ch5(9-13),Ch6(1-10) | Quiz 8,HW9 due on 4/26 |
| 24 | T | 4/28 | cholesky factorization, least squares | ||
| 25 | R | 4/30 | line fitting, svd | HW11: Ch6(11-18, 20-22) | Quiz 9,HW10 due on 5/3 |
| 26 | T | 5/5 | svd | ||
| 27 | R | 5/7 | review, final | HW11 due on 5/10 |