# NVIDIA FLARE

> NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK for federated learning and other federated-computing applications, from local development through production deployment.


2025 NVIDIA

## Pages in this subsection

- [Hello World Examples](hello_world_examples.md): Hello World examples can be run from the hello_world notebook.
- [Hello NumPy](hello_numpy.md): This example demonstrates how to use NVIDIA FLARE with NumPy to train a simple model using federated...
- [Hello Cross-Site Validation](hello_cross_val.md): Before jumping into this guide, make sure you have an environment
- [Hello PyTorch with the Job API](hello_pt_job_api.md): The maintained Hello PyTorch Job API walkthrough is now consolidated in
- [Hello TensorFlow with Job API](hello_tf_job_api.md): This example uses TensorFlow/Keras and NVIDIA FLARE’s Job and Client APIs to
- [FL Algorithms](fl_algorithms.md): In NVIDIA FLARE, FedAvg is implemented through the Scatter and Gather Workflow. In the federated ave...
- [Federated Statistics Overview](federated_statistics_overview.md): NVIDIA FLARE will provide built-in federated statistics operators (controllers and executors) that c...
- [FL Experiment Tracking with TensorBoard Streaming](tensorboard_streaming.md): In this exercise, you will learn how to stream TensorBoard events from the clients
- [FL Experiment Tracking with MLflow](fl_experiment_tracking_mlflow.md): The example for experiment tracking with MLflow has clients streaming their statistics to the server...
- [Accessing the results](access_result.md): The results of each job will usually be stored inside the server side workspace.
- [Medical Image Analysis](medical_image_analysis.md): Medical imaging examples on GitHub:
- [Running the FL System](run_fl_system.md): Now you can use admin command prompt to submit and start this example job.
- [Shutdown FL system](shutdown_fl_system.md): Once the FL run is complete and the server has successfully aggregated the client’s results after al...
- [Tutorial Notebooks](tutorial_notebooks.md): Tutorial notebooks on GitHub:

## Optional

- [Top-level llms.txt](../llms.txt): Complete documentation index.