Build accurate, personalized models for recommender systems using
Weights & Biases

Build, manage, and deploy cutting-edge recommender systems and drive top consumer branding in streaming services, e-commerce, social media, and more.

Trusted by the teams building the largest models

Square, an industry leader in business payments and solutions, relies on Weights & Biases to build LLM recommendation systems to help small and medium sized businesses communicate with their customers.

StitchFix, the market leader innovator in personal styling service, uses Weights & Biases to monitor the fine-tuning of their OpenAI models to help improve how to understand client feedback.

Pandora (Sirius XM Radio), a pioneer in personalized music recommendations, saves a lot of time – and headaches – by creating hyperparameter sweeps that run automatically in Weights & Biases.

Scale your models to service your growing customer base

As your number of customers and users grow, the complexity of the recommender system will scale exponentially with the number of large scale models feeding into the system. Weights & Biases is built to handle large-scale, complex models, allowing you to feed and train more data and run significantly more experiments to continuously fine-tune the personalizations your system serves up.

Move fast without worrying about what’s being left behind

Models for recommender systems need to be built, maintained, and updated as quickly as consumer trends and choices are changing. Weights & Biases allows ML practitioners to move fast in building and deploying models faster than ever, with worrying about critical mistakes or reproducibility gaps thanks to enterprise-grade model versioning.

Examples

Build trusted, explainable models

Personalizations from recommender systems are all about building trust with your customers. With Weights & Biases’ continuous insights into model behavior and bias detection, you can be sure that your models and systems will be explainable and fair. This not only builds credibility with users but also checks off important compliance requirements with regulatory bodies.

Examples

SOC 2 compliance, encryption, security, and more

Weights & Biases prioritizes data privacy and security with our SOC 2 Type II certification, encrypted data, endpoint, and network, and robust security controls. When you’re working with sensitive, personal customer data and shopping habits, you can trust us to keep that data and those models safe.

Work securely in your chosen environment

Deploy Weights & Biases in whatever manner makes the most sense for your Recommender Systems, with deployment options including a multi-tenant cloud, a single-tenant cloud, and customer-managed private deployments. Whether you need a fast and flexible deployment, or have more stringent enterprise-level security requirements, we can provide custom permissions and data obfuscation to fit the privacy protocols you need.

See Weights & Biases in action

Recommender Systems using Hugging Face & NVIDIA

Leveraging JAX for Recommendation Systems

GNNs for Recommendation with PyG

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

Weave

Traces

Explore and debug LLMS

Evaluations

Rigorous evaluations of GenAI applications

Core

Artifacts

Version and manage your ML pipelines

Tables

Visualize and explore your ML data

Reports

Document and share your ML insights

SDK

Log ML experiments and artifacts at scale

Use cases

Industries

Build accurate, personalized models for recommender systems using
Weights & Biases

Trusted by the teams building the largest models

Scale your models to service your growing customer base

Move fast without worrying about what’s being left behind

Build trusted, explainable models

SOC 2 compliance, encryption, security, and more

Work securely in your chosen environment

See Weights & Biases in action

Recommender Systems using Hugging Face & NVIDIA

Leveraging JAX for Recommendation Systems

GNNs for Recommendation with PyG

The Weights & Biases platform helps you streamline your workflow from end to end

The Weights & Biases platform helps you streamline your workflow from end to end

Models

Experiments

Sweeps

Registry

Automations

Weave

Traces

Evaluations

Core

Artifacts

Tables

Reports

SDK

Build trusted, explainable models for Recommender Systems with Weights & Biases

The Platform

Article

Resources

Company

Use cases

Industries

Use cases

Industries

Build accurate, personalized models for recommender systems using Weights & Biases

Trusted by the teams building the largest models

Scale your models to service your growing customer base

Move fast without worrying about what’s being left behind

Build trusted, explainable models

SOC 2 compliance, encryption, security, and more

Work securely in your chosen environment

See Weights & Biases in action

Recommender Systems using Hugging Face & NVIDIA

Leveraging JAX for Recommendation Systems

GNNs for Recommendation with PyG

The Weights & Biases platform helps you streamline your workflow from end to end

The Weights & Biases platform helps you streamline your workflow from end to end

Models

Weave

Core

Build trusted, explainable models for Recommender Systems with Weights & Biases

The Platform

Article

Resources

Company

Use cases

Industries

Build accurate, personalized models for recommender systems using
Weights & Biases