This page is for readers who have not programmed before. You can run the first laboratory without installing anything. A longer book on data and dynamical systems, when you want one, is Brunton & Kutz (2022).
Words you will see¶
| Word | Meaning in these notes |
|---|---|
| Python | The programming language used in the labs |
| Notebook | A web page made of text boxes and code boxes. You read the text and run the code |
| Cell | One box. A text cell explains. A code cell computes |
| Run | Ask the computer to carry out that one cell. Use the play button, or press Shift+Enter |
| Kernel | The live Python session behind the notebook. Restarting the kernel forgets earlier cells, so you run the notebook again from the top |
| Package | Reusable code with a name. The teaching package in this book is called sciml_ps |
| Error | A red message. Read the last line. It usually says what was missing |
The first-lab walkthrough points at each one while you use it.
Run one notebook today¶
Open Your first lab.
Follow the Google Colab steps (a free browser session). Binder is the fallback if you prefer not to use a Google account.
Stop when you see a plot of rotor angle against time. That means the notebook ran.
What you should see after the setup cell: a line that ends with imports ok.
Practice after that¶
The four notebooks under Preparation are the next practice (arrays, a small differential equation, a tiny neural fit, gradients). They are still stubs. Use Lab 1 for a complete run, and treat Preparation as optional drills while those notebooks grow.
If a later chapter feels hard only because of the code, come back to this page and to the walkthrough’s troubleshooting list.
Where to go next¶
| If you also need | Read |
|---|---|
| The power-system story | Power systems for ML people |
| The learning story | Machine learning for power-systems people |
| A map of the whole book | Start here |
- Brunton, S. L., & Kutz, J. N. (2022). Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control (Second). Cambridge University Press. 10.1017/9781009089517