Ece3
The lectures present concepts from linear algebra, such as matrix computations, systems of linear equations, eigenspace decomposition, inner-product, orthogonality, least-squares and linear regression. Students actively engage with the materials with an introduction to Python programming
Install / Use
/learn @geometric-intelligence/Ece3README
ECE-3: Python Programming for Science & Engineering
Welcome!
This is the GitHub repository for the course:
ECE-3: Python Programming for Science & Engineering.
Interact with the course contents
You can access and run the lecture slides and lab notebooks by clicking on the Binder link below.
Outline
- Unit 01: Welcome to Python
- Unit 02: Computing with Data in Python
- Unit 03: Summarizing and Visualizing Data in Python
- Unit 04: Predicting from Data with Machine Learning in Python
Textbooks
The content of this class relies on the following excellent textbooks:
- Unit 01: Think Python by Downey.
- Unit 02-03: Introduction to Applied Linear Algebra, by Boyd & Vandenberghe.
- Unit 04: Introduction to Statistical Learning by James, Witten, Hastie, Tibshirani, Taylor.
The textbooks are freely available online.
Syllabus
More details are on the syllabus.
Run the jupyter notebook slides
In your terminal:
conda env create -f environment.yml
python -m ipykernel install --user --name=ece3 --display-name "Python (ece3)"
jupyter notebook
Then open the slides of interest, and click Enter/Exit Rise Slideshow Icon.
Best wishes for the new quarter! ☺
