In the past, I eschewed Excel. However, I now use Excel frequently and enjoy it very much! What changed?
Starting my Excel Journey During last academic year, my degree program required me to do three laboratory rotations. My first two rotations were computational where I did work in bioinformatics of biochemistry and genetics data. However, for my third rotation, I choose a rotation that was 100% biology lab bench work, with no computational component.
In these animations, I used one- and two-dimensional Gaussian functions to animate a couple of YouTube shorts! Check them out here.
One-dimensional Gaussian
Two-dimensional Gaussian
View the Python code which made the animations on GitHub
In this video I demonstrate calculations of quantum harmonic oscillator in Excel.
For the best experience, I recommend viewing it full screen!
This video is about creating normally and uniformly distributed random values in Excel.
I recommed viewing it full screen for the best experience!
Functions demonstrated: SEQUENCE(), RAND(), RANDBETWEEN(), RANDARRAY(), NORM.DIST(), NORM.INV().
This video is an example of creating a heatmap of a 2D Gaussian function in Excel using conditional formatting.
I recommed viewing it full screen for the best experience!
Functions demonstrated: SEQUENCE().
Introduction On Kaggle, I found a dataset of customer churn data for a fictitious bank deposited by Radesheshyam Kollipara. It is a simple dataset of just one table. The exercise analyzes which customers are most likely to exit the bank.
The table’s most critical column is the “Exited” column, which in the original data is one if the customer left the bank and 0 if the customer stayed. It also contains other information about each customer and their accounts.
Simple Gradient Descent with Python This is a simple polynomial gradient descent. It is a naive implmentation that is not optimized or vectorized. It is meant to be a simple demo on how gradient descent can be accomplished. To keep it simple, it uses base Python. I don’t intend for it to be used for anything important!
Some Equations The “target” polynomial that will be fitted is defined as Eqn. 1:
