es157-notebooks

For the Fall 2020 edition of Harvard's ES 157 we created notebooks to work through in sections. The class is called "Biological Signal Processing" and studies signal processing and probabilistic approaches towards the modeling and analysis of physiological signals. To that end, the notebooks aimed to familiarize students with coding and give them practical experience with the algorithms and techniques that they learned in the class.

Specifically, the notebooks grapple with the following concepts and themes

• notebook1: General introduction to signals and signal processing in python.
• notebook2: Introduction to impulse responses, convolution, and linearity and time-invariance.
• notebook3: Modeling COVID cases by combining concepts from probability and signal processing.
• notebookX: Using probability and statistics in python, intuition behind the Central Limit Theorem, and the Secretary problem.
• notebookY: Exploring the differences between the maximum likelihood and maximum a posteriori estimates, and a visual breakdown of Principal Component Analysis.

We hope you find these notebooks useful.

Stay safe! 👋