What is Flower?
It is an open-source framework for training AI on distributed data using federated learning. Federate any workload, any ML framework, and any programming language.
Flower is a tool in the Machine Learning Tools category of a tech stack.
Flower is an open source tool with 4K GitHub stars and 721 GitHub forks. Here’s a link to Flower's open source repository on GitHub
Who uses Flower?
Developers
Flower Integrations
Python, TensorFlow, NumPy, PyTorch, and Keras are some of the popular tools that integrate with Flower. Here's a list of all 5 tools that integrate with Flower.
Flower's Features
- ML framework agnostic
- Cloud, mobile, edge & beyond
- Platform independent
- Extendable
Flower Alternatives & Comparisons
What are some alternatives to Flower?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
CUDA
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
Related Comparisons
No related comparisons found