Dvc + Streamlit = ❤️

This repository is an example that illustrate how dvc together with streamlit can help tracking the model performance during R&D exploration.

It contains scripts that:

1. download the cat_vs_dogs dataset
2. split the dataset into train/val/test subsets
3. train a classifier using transfer learning from a pre-trained network.
4. compute evaluation metrics

The python code is not the purpose of this repository. It is adapted from the transfer learning Tensorflow tutorial.

Data, metrics, model weights produced during the training and evaluation processed are tracked using dvc while a streamlit app allows to visually explore model predictions and compare trained models.

Installation

Requirements

• python > 3

Install dependencies with pip:

pip install -r requirements.txt