You can run the whole notebook in Colab without issue. Getting helper scripts from Github repo, downloading datasets, and install required packages are all handled.
- Clone repository and change directory to local copy
- Create a conda environment
conda create --name bayesian_nn - Activate conda environment
conda activate bayesian_nn - Install required libraries
pip install -r requirements.txt - Run jupyter lab
jupyter lab - Open
Dropout as Bayesian Approximation.ipynb
Data is passed through the model with Dropout turned on
during the inference step for multiple times. The resulting
probability distributions are what the model produce over
multiple passes.
When the model is uncertain:
When the model is certain:
High certainty:
Extremely high certainty:
