How I won my 41st bronze medal on a Kaggle playground competition with a Jax regression neural network

I have decided to write a blog post on how I won a bronze medal using a Jax regression neural network because I very surprisingly won a bronze medal for the work that I carried out on it. In an earlier post, I wrote about this same competition question using a linear regression model in Jax, and that blog post can be found here:- https://medium.com/@tracyrenee61/predict-on-the-probability-of-a-person-smoking-using-jax-linear-regression-9eda2abf5805

If the reader would like to gain a greater understanding of regression neural networks, he can refer to the post that I have written where I made predictions on the Boston house price dataset:- https://medium.com/@tracyrenee61/use-jaxs-regression-neural-network-to-predict-on-boston-house-prices-fef89b4f9321

I am not quite sure why I was given a bronze medal for this particular piece of work, and I suspect it was because I attempted to create a regression neural network. Regardless of the reasons, I have decided to post the code I used for this endeavour to make it available to other people.

I have written the program in Kaggle’s free online Jupyter Notebook and it is stored in my Kaggle account.