Browse by category
🙋♀️ Introduction to FlowerAn overview of the Flower framework, its purpose, and its significance in the realm of federated learning. This category will introduce users to the unified approach of federated learning, analytics, and evaluation that Flower offers.🌻 Getting Started with FlowerDetailed instructions and guides on how to install and set up Flower. This will include information on compatibility with various machine learning frameworks like PyTorch, TensorFlow, and Hugging Face, and how to federate existing ML projects.👩💻 Federated Learning TutorialsA series of tutorials that delve into the fundamentals of Federated Learning and its implementation using Flower. Topics might include the basics of federated learning, federated evaluation, federated analytics, and differential privacy.💡 Advanced Flower StrategiesIn-depth guides and tutorials on customizing federated learning strategies with Flower. This will cover topics like server-side parameter evaluation, sending/receiving arbitrary values to/from clients, and scaling federated learning.❓ Why Choose Flower?Insights into the unique features and benefits of the Flower framework. This will highlight its scalability, compatibility with various ML frameworks, platform independence, and its journey from research to production.👥 Community and FeedbackInformation on how users can join the Flower community, provide feedback, and contribute to its development. This will also include links to their official channels like GitHub and Slack.
Popular articles