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Visually probe the behavior of trained machine learning models, with minimal coding. A key challenge in developing and deploying responsible Machine Learning (ML) systems is understanding their performance across a wide range of inputs. Using WIT, you can test performance in hypothetical situations, analyze the importance of different data features, and visualize model behavior across multiple mod

deeplearn.js is an open-source library that brings performant machine learning building blocks to the web, allowing you to train neural networks in a browser or run pre-trained models in inference mode. We provide an API that closely mirrors the TensorFlow eager API. deeplearn.js was originally developed by the Google Brain PAIR team to build powerful interactive machine learning tools for the bro

The power of machine learning comes from its ability to learn patterns from large amounts of data. Understanding your data is critical to building a powerful machine learning system. Facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets. Get a sense of the shape of each feature of your dataset using Facets Overview, or explore individual observat