We use W&B for all our large-scale, serious experiments. The scalability, the customizability, live monitoring, not frozen reports of the conclusion — these features vastly improved our productivity.
See the predictions and ground truth of your model in our interactive interface. You can explore the different predictions that your model makes over time, or compare across different model versions.
Our live dashboard allows you to collect results across members of your team and display them in one place. You can also build reports to share results across teams in your organization.
We work with some of the largest machine learning teams in the world, and our product is built to scale to millions of experiments. We natively support distributed training.
Decide on criteria, visualize performance, and customize queries to compare your model variants and focus on the right ones.
Track everything in one place. W&B automatically logs every input into your training for regulatory compliance and reproducibility.
Use the Keras callback to automatically save all the metrics and the loss values tracked in model.fit.
W&B provides first class support for PyTorch. To automatically log gradients and store the network topology, you can call watch and pass in your PyTorch model.
If you're already using TensorBoard, it's easy to integrate with wandb.
Compare how different models perform on 3D object detection problems. In our interactive visualizations, you can explore point cloud scenes and compare ground truth and prediction bounding boxes.
Dynamically visualize the results of image segmentation models.