#Interactive Visualization

This interactive visualization tool simplifies Convolutional Neural Networks (CNNs) for learners through engaging graphics. Created by researchers from Georgia Tech and Oregon State, it features a live demo, local execution options, and resources for customizing with individual CNN models or image classes. The system acts as an educational resource for those exploring deep learning without extensive technical knowledge, making CNN structures and processes more accessible.

Dodrio assists NLP researchers in analyzing transformer model attention weights with a focus on linguistic context. It provides an interactive demo, comprehensive setup instructions, and is acknowledged in leading academic discussions, facilitating a deeper understanding of model behavior.

LIT is an open-source tool for interactive analysis of machine learning models, handling text, image, and tabular data. It supports local explanations, aggregate analysis, and counterfactual generation. Compatible with major frameworks like TensorFlow and PyTorch, LIT allows side-by-side model comparisons and is suitable for diverse model types. The tool integrates easily into environments like Colab and Jupyter, offering a browser-based UI for analyzing model behavior.