TensorBoard.dev allows you to upload and share TensorBoards and visualize model graphs and metrics Credit: ipopba / Getty Images Google has unveiled TensorBoard.dev, an online platform where data scientists, researchers, machine learning practitioners, and software developers can share machine learning experiments and collaborate on machine learning projects. Now in a beta release stage, TensorBoard.dev lets users upload machine learning experiments for sharing with anyone. The platform leverages the TensorBoard visualization toolkit, which works with Google’s TensorFlow library for machine learning and deep learning. TensorBoard allows users to track model training metrics such as accuracy and loss, visualize the model graph, and view histograms of weights, biases, and other tensors. Users can upload TensorBoard logs for free and share the URL, although there is a limit on storage. Data uploaded will be visible to anyone with a link, so it is not advisable to upload sensitive data. The TensorBoard.dev preview starts out with the TensorBoard scalar dashboard, for visualizing key machine learning metrics. Over time, more functionality will be added, with the goal of improving the sharing experience. How to access the TensorBoard.dev preview You can access the TensorBoard.dev preview online. A Google Account is required to use TensorBoard.dev. Development ToolsMachine LearningData ScienceSoftware DevelopmentAnalyticsCloud Computing