Weights & Biases (W&B) is a developer platform designed to help ML practitioners build better models faster. It is trusted by over 500,000 ML practitioners at 700+ companies and research institutions worldwide. W&B provides a central dashboard to track hyperparameters, system metrics, and predictions, allowing users to compare models live and share their findings. With W&B, developers can track experiments, version and iterate on datasets, evaluate model performance, reproduce models, and manage ML workflows end-to-end. It supports popular ML libraries and frameworks like TensorFlow, PyTorch, Keras, Scikit-learn, and more. The platform offers features such as experiment tracking, collaborative dashboards, dataset and model versioning, interactive data visualization, hyperparameter optimization, and automated ML workflows. Users can analyze data and uncover insights in a centralized location, evaluate and deploy models with confidence, and easily collaborate with team members. W&B integrates with various ML libraries, repositories, training environments, workflow orchestration tools, and inference environments, providing a unified interface over any ML infrastructure. The platform aims to streamline the ML workflow, eliminate redundant work, and make ML projects more reproducible and discoverable. It has been praised by customers for its flexibility, performance, and user experience. Additionally, W&B offers a community for ML practitioners, a podcast, webinars, and a blog to stay connected with the ML community. Overall, Weights & Biases is a comprehensive and reliable platform that empowers ML practitioners to streamline their workflows and make better decisions throughout the ML lifecycle.