Flower Examples Documentation¶
Welcome to Flower Examples’ documentation. Flower is a friendly federated AI framework.
Join the Flower Community¶
The Flower Community is growing quickly - we’re a friendly group of researchers, engineers, students, professionals, academics, and other enthusiasts.
Quickstart Examples¶
Flower Quickstart Examples are a collection of demo projects that show how you can use Flower in combination with other existing frameworks or technologies.
Advanced Examples¶
Advanced Examples are mostly for users that are both familiar with Federated Learning but also somewhat familiar with Flower’s main features.
Title |
Framework |
Dataset |
Tags |
---|---|---|---|
Federated Learning with PyTorch and Flower (Advanced Example) |
Fashion-MNIST |
advanced, vision, fds, wandb |
|
Federated Learning with TensorFlow/Keras and Flower (Advanced Example) |
keras, tensorflow |
Fashion-MNIST |
advanced, vision, fds, wandb |
advanced, vision, fds |
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advanced, secure_aggregation, privacy |
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vertical, tabular, advanced |
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Federated Learning with XGBoost and Flower (Comprehensive Example) |
advanced, classification, tabular |
Other Examples¶
Flower Examples are a collection of example projects written with Flower that explore different domains and features. You can check which examples already exist and/or contribute your own example.
Title |
Framework |
Dataset |
Tags |
---|---|---|---|
mobile, vision, sdk |
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Flower Android Client Example with Kotlin and TensorFlow Lite 2022 |
mobile, vision, sdk |
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basic, vision, fds |
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Custom Metrics for Federated Learning with TensorFlow and Flower |
basic, vision, fds |
||
mods, monitoring, app |
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Fashion-MNIST |
basic, vision, embedded |
||
Federated Survival Analysis with Flower and KaplanMeierFitter |
estimator, medical |
||
Flower Example on MNIST with Differential Privacy and Secure Aggregation |
DP, SecAgg, vision, fds |
||
basic, tabular, fds |
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colab, vision, simulation |
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Fashion-MNIST |
vision, simulation, video-tutorial |
||
Leveraging Flower and Docker for Device Heterogeneity Management in Federated Learning |
deployment, vision, tutorial |
||
llm, nlp, LLama |
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finetuning, vision, fds |
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mobile, vision, sdk |
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Training with Sample-Level Differential Privacy using Opacus Privacy Engine |
DP, DP-SGD, basic, vision, fds, privacy |
||
basic, vision, fds |
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basic, vision, fds |
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Flower Logistic Regression Example using scikit-learn and Flower (Quickstart Example) |
basic, vision, logistic regression, fds |
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Training with Sample-Level Differential Privacy using TensorFlow-Privacy Engine |
DP, DP-SGD, basic, vision, fds, privacy |
||
finetuning, speech, transformers |