Improve model predictions and drive business value with Weights & Biases
From classification use cases like spam and fraud detection, medical diagnostics, and sentiment analysis to common regression tasks such as financial forecasting and price prediction, the Weights & Biases platform makes comparing, iterating, and fine-tuning model performance easy.
Trusted by the leading teams across industries—from financial institutions to eCommerce giants
Socure, a graph-defined identity verification platform, uses Weights & Biases to streamline its machine learning initiatives, keeping everyone’s wallets a little more secure.
Qualtrics, a leading experience management company, uses machine learning and Weights & Biases to improve sentiment detection models that identify gaps in their customers’ business and areas for growth.
Invitae, one of the fastest-growing genetic testing companies in the world, use Weights & Biases for medical record comprehension leading to a better understanding of disease trajectories and predictive risk
Rich & interactive visualizations for instant insights
Iterate quickly, and get insights instantly in a central, collaborative dashboard. With interactive, customizable queries and configurable tables, Weights & Biases makes it easy to understand your data—from medical images to tweet sentiment.
Automate and scale ML workflows
Manage the entire model lifecycle development process in one place
Collaboratively share results across vast organizations
See Weights & Biases in action
Predicting Lung Disease with Binary Classification
Tables Tutorial: Visualize Text Data and Predictions
DeepForm: Track Political Advertising With Deep Learning
The Weights & Biases platform helps you streamline your workflow from end to end
Models
Experiments
Track and visualize your ML experiments
Sweeps
Optimize your hyperparameters
Registry
Publish and share your ML models and datasets
Automations
Trigger workflows automatically
Launch
Package and run your ML workflow jobs
Weave
Traces
Explore and
debug LLMs
Evaluations
Rigorous evaluations of GenAI applications