Experimenting with Bayesian neural networks (BNN).

In this repo I experiment with Bayesian neural network. The idea is to create a simple scenario, i.e predict if I would go for a walk.

Step 1: create dummy data

I create a dummy data based on some realistic temperature values for my location. I use beautifulsoup to scrape atable that shows temperature for day, night, and how many days it rains, for each month.

This pair plot is created using creatdummy_data.ipynb.

Step 2: Train BNN on the dummy data

In this step I create and train the BNN.

Step 3: Do predictions, testing, & fine tuning

Here I create certain scenarios and test out what my BNN does. Here I take the opportunity to explore the decision make through the nodes, and explore the network.

In this step, I predict if I would go for a walk through the months.

Step 4: ML & Data Ops

In this step I use github actions to add data everyday