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Flower 1.5.0
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Flower 1.5.0

Tutorial

  • What is Federated Learning?
  • An Introduction to Federated Learning
  • Strategies in Federated Learning
  • Building a Strategy
  • Client and NumPyClient

Quickstart tutorials

  • Quickstart PyTorch
  • Quickstart TensorFlow
  • Quickstart 🤗 Transformers
  • Quickstart JAX
  • Quickstart Pandas
  • Quickstart fastai
  • Quickstart PyTorch Lightning
  • Quickstart MXNet
  • Quickstart scikit-learn
  • Quickstart XGBoost
  • Quickstart iOS

How-to guides

  • Install Flower
  • Configure Clients
  • Strategies
  • Implementing Strategies
  • Save Progress
  • Saving and Loading PyTorch Checkpoints
  • Monitor Simulation
  • SSL-enabled Server and Client
  • Example: Walk-Through PyTorch & MNIST
  • Example: PyTorch - From Centralized To Federated
  • Example: MXNet - Run MXNet Federated
  • Example: JAX - Run JAX Federated
  • Example: FedBN in PyTorch - From Centralized To Federated
  • Virtual Env Installation
  • Upgrade to Flower 1.0

Explanations

  • Evaluation
  • Differential Privacy Wrappers in Flower

API reference

  • flwr (Python package)
  • Flower CLI commands

Reference docs

  • Code examples
  • Telemetry
  • Changelog
  • FAQ

Flower Baselines

  • Using Baselines
  • Contributing Baselines

Contributor guide

  • First time contributors
  • Getting Started (for Contributors)
  • Good First Contributions
  • Contributor setup
  • How to write documentation
  • Flower Architecture
  • Secure Aggregation Protocols
  • Release Process
  • Creating New Messages
  • VS Code Remote - Containers
  • FED - Flower Enhancement Doc
    • FED Template
    • Flower Enhancement Doc
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FED - Flower Enhancement Doc#

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