[Numerical Modeling 7] A quick look at SymPy for symbolic computation in Python

Symbolic computation is the kind of manipulation we do commonly on mathematical expressions in calculus, like the ones we used to do in high school for differentiation and integration. You may find it a bit weird for a computer program to have such an ability, but this symbolic algebraic computing has been around for several years. It has become mature in recent decade, and there are several options available for getting started with, one of the best of which is SymPy in Python world. Let’s see what it has to say in action. Educational Materials: In order to follow the videos, you need the educational materials, which are provided as a set of Jupyter Notebooks. You can find the materials at http://tuxriders.com/videos/numerical... and https://github.com/TuxRiders/numerica... Topics covered: 🎯 Introducing symbolic computation 🎯 Symbolic expressions and their numerical evaluation 🎯 Algebraic manipulations 🎯 Differentiation and integration 🎯 Limits and series 🎯 Solving equations symbolically Lecturer: Mojtaba Barzegari https://mbarzegary.github.io/ To learn more about the goals of the TuxRiders project, please visit our website at http://tuxriders.com. Apology for the noise in the video: we apologize for the noise you hear at some part of the video. This video is recorded on a super windy day in the windy Netherlands 😊. This has affected the quality of the sound in some parts of the video. We didn’t notice it till the time of editing.