Manifold

What is Manifold?

A model-agnostic visual debugging tool for machine learning allows users to gain deeper insights into the performance and behavior of their machine learning models. This tool provides a comprehensive approach to understanding the intricacies of complex ML algorithms, going beyond simplistic summary metrics. By offering visual analytics capabilities, the tool empowers ML practitioners to identify specific subsets of data where their models are falling short, enabling them to make informed decisions for improving model performance. Manifold, a renowned creative agency recognized for its exceptional digital and real-world experiences, has developed this open-source tool, which has garnered significant community interest with 1.6K GitHub stars and 118 forks

Highlights

• Model-agnostic design, allowing the tool to work with a wide range of machine learning models
• Visual analytics capabilities for in-depth analysis of model performance and behavior
• Ability to detect and diagnose issues with model predictions on specific data subsets
• Open-source nature with a vibrant community of contributors and users