Foundations-of-Applied-Mathematics / DataLinks
Data for the Foundations of Applied Mathematics lab curriculum.
☆27Updated last year
Alternatives and similar repositories for Data
Users that are interested in Data are comparing it to the libraries listed below
Sorting:
- Specification files for the Foundations of Applied Mathematics lab curriculum. https://foundations-of-applied-mathematics.github.io/☆54Updated last year
- Program files from MATLAB Guide, Third Edition☆29Updated 8 years ago
- Labs for the Foundations of Applied Mathematics curriculum.☆226Updated 9 months ago
- A cheatsheet for Python and Julia☆155Updated last year
- Extra materials for *Fundamentals of Numerical Computation* by Driscoll and Braun.☆169Updated last month
- Python programs and data files for "Introduction to Python for Science and Engineering" by David J. Pine☆29Updated 5 years ago
- These are the jupyter notebooks used for intro tutorials to teach Julia☆71Updated 6 years ago
- Advanced-Programming☆25Updated last year
- ☆22Updated 4 years ago
- Resources for the book "Programming for Computations" by S. Linge and H. P. Langtangen☆124Updated 3 years ago
- Julia code for the book Numerical Linear Algebra☆126Updated 2 years ago
- Advanced Topics in Scientific Computing with Julia☆91Updated 5 years ago
- A Deep Introduction to Julia for Data Science and Scientific Computing☆253Updated 3 years ago
- ☆75Updated 8 years ago
- 3 Hour Workshop for JuliaCon 2021☆68Updated 3 years ago
- Welcome to DataFrames.jl with Bogumił Kamiński☆129Updated 2 years ago
- Source code for some notes for the mathematical tripos.☆22Updated 6 years ago
- A set of introductory exercises for Julia. Based on [100 NumPy Exercises](https://github.com/rougier/numpy-100).☆138Updated 2 years ago
- My cheatsheets☆110Updated 2 years ago
- MATLAB codes accompanying "Numerical Linear Algebra Theory" by Larisa Beilina, Evgenii Karchevskii, and Mikhail Karchevskii☆16Updated 8 years ago
- Scientific Computing with Python for beginners.☆54Updated last week
- Julia high Performance Programming by Packt☆24Updated 2 years ago
- slides + Jupyter notebooks for the Stony Brook University "Python for Scientific Computing" class.☆81Updated last week
- 18.303 - Linear PDEs course☆144Updated last year
- A solver for nonlinear, dynamic, stochastic, rational expectations equilibrium models☆20Updated 3 years ago
- JuliaCon 2022 - Introduction to Julia Tutorial☆61Updated 2 years ago
- Codes for the book "Julia for Data Analysis"☆217Updated 5 months ago
- Julia course: from total beginner to power user!☆11Updated 5 months ago
- Julia 1.0 Programming Second Edition, published by Packt☆25Updated 4 years ago
- Data science and numerical computing with Julia☆58Updated 5 years ago