There are 2 repositories under model-visualization topic.
Debugging, monitoring and visualization for Python Machine Learning and Data Science
Entity Framework Core Power Tools - reverse engineering, migrations and model visualization in Visual Studio & CLI
moDel Agnostic Language for Exploration and eXplanation
📍 Interactive Studio for Explanatory Model Analysis
A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN
Visualize correlations between variables
Triplot: Instance- and data-level explanations for the groups of correlated features.
This repo helps to track model Weights, Biases and Gradients during training with loss tracking and gives detailed insight for Classification-Model Evaluation
Display outputs of each layer in CNN models
ReactJS dashboard to visualize the model results of ShipCohortStudy
Develop and deploy to the web a machine learning model to score banking credit applications
Georgia Institute of Technology: DEPENDENCY AMONG ECONOMIES, MEASURED BY MAIN STOCK INDICES.
A Pandemic Simulation ApplIication, for simulating viruses
Code to visualize how different layers view the input when the output is changed. Also visualize the salient features as seen by the input image
Yellowbrick wraps the scikit-learn and matplotlib to create publication-ready figures and interactive data explorations. It is a diagnostic visualization platform for machine learning that allows us to steer the model selection process by helping to evaluate the performance, stability, and predictive value of our models and further assist in diagnosing the problems in our workflow.
This repository provides a collection of code and implementations for various chaos theory models. It aims to facilitate the understanding and exploration of chaos theory concepts and inspire further research and experimentation in this field.