Experiment tracking, hyperparameter optimization, model and dataset versioning
A system of record for your model results
Add a few lines to your script, and each time you train a new version of your model, you'll see a new experiment stream live to your dashboard.
Learn more →Try dozens of model versions quickly
Optimize models with our massively scalable hyperparameter search tool. Sweeps are lightweight, fast to set up, and plug in to your existing infrastructure for running models.
Learn more →Lightweight model and dataset versioning
Save every detail of your end-to-end machine learning pipeline — data preparation, data versioning, training, and evaluation.
Learn more →Explore results and share findings
It's never been easier to share project updates. Explain how your model works, show graphs of how model versions improved, discuss bugs, and demonstrate progress towards milestones.
Learn more →Seamlessly share progress across projects
Manage team projects with a lightweight system of record. It's easy to hand off projects when every experiment is automatically well documented and saved centrally.
Effortlessly capture configurations
With Weights & Biases experiment tracking, your team can standardize tracking for experiments and capture hyperparameters, metrics, input data, and the exact code version that trained each model.
Identify performance issues quickly
Focus your team on the hard machine learning problems, and let Weights & Biases take care of the legwork of tracking and visualizing performance metrics, example predictions, and even system metrics to identify performance issues.
Share updates across your organization
It's never been easier to share project updates. Explain how your model works, show graphs of how model versions improved, discuss bugs, and demonstrate progress towards milestones.
A system of record for your model results
Add a few lines to your script, and each time you train a new version of your model, you'll see a new experiment stream live to your dashboard.
Learn more →Try dozens of model versions quickly
Optimize models with our massively scalable hyperparameter search tool. Sweeps are lightweight, fast to set up, and plug in to your existing infrastructure for running models.
Learn more →Lightweight model and dataset versioning
Save every detail of your end-to-end machine learning pipeline — data preparation, data versioning, training, and evaluation.
Learn more →Explore results and share findings
It's never been easier to share project updates. Explain how your model works, show graphs of how model versions improved, discuss bugs, and demonstrate progress towards milestones.
Learn more →Protect and manage valuable IP
Use this central platform to reliably track all your organization's machine learning models, from experimentation to production. Centrally manage access controls and artifact audit logs, with a complete model history that enables traceable model results.
Reliable records for auditing models
Capture all the inputs, transformations, and systems involved in building a production model. Safeguard valuable intellectual property with all the necessary context to understand and build upon models, even after team members leave.
Unlock productivity, accelerate research
With a well integrated pipeline, your machine learning teams move quickly and build valuable models in less time. Use Weights & Biases to empower your team to share insights and build models faster.
Install in private cloud and on-prem
Data security is a cornerstone of our machine learning platform. We support enterprise installations in private cloud and on-prem clusters, and plug in easily with other enterprise-grade tools in your machine learning workflow.
"W&B was fundamental for launching our internal machine learning systems, as it enables collaboration across various teams."
"W&B allows us to scale up insights from a single researcher to the entire team and from a single machine to thousands."
"W&B is a key piece of our fast-paced, cutting-edge, large-scale research workflow: great flexibility, performance, and user experience."
Once you’re using W&B to track and visualize ML experiments, it’s seamless to create a report to showcase your work.
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