This App aims to visualize changes in filters and representation produced by a Convolutional Artificial Neural Network (LeNet-5) while learning how to classify different clothing categories present in the Fashion-MNIST dataset.
For maximizing the observed differences and reducing memory overhead, the observed training period is represented by the sequence of random batches observed during a single training epoch.
- Script for trainining-on-batch of LeNet-5 on Fashion-MNIST.
- Extracting learned filters over training.
- Extracting learned embeddings oser training.
- Running AlignedUMAP ovser sequence of extracted embeddings.
- Streamlit App
- Visulize changes in learned filters over training.
- Visulize changes in UMAP reduction of learned embedding over training.
Open the app clicking on the streamlit badge on top of this README.