This tutorial introduces how to make your data exploration and model building process more interactive and exploratory by using the combination of JupyterLab, HoloViews, and PyTorch. I will focus on the problem of classfying different types of roads on satellite images, defined as a "multi-class semantic segmentation problem". Starting from the data exploration to the trained model understanding, we will cover different ways to explore the data and models with simple, interactive GUIs in Jupyter notebooks. Specifically, the tutorial covers, with the emphasis on the experimental nature of model building:
- how to make your data exploration more intuitive and experimental using HoloViews libraries
- how to turn your model script into a simple GUI that allows interactive hyperparameter tuning and model exploration
- how to monitor the training process in realtime
- how to quickly build a GUI tool to inspect the trained models in the same Jupyter notebook