What is MetisFL?
It is a federated learning framework that allows developers to federate their machine learning workflows and train their models across distributed datasets without having to collect the data in a centralized location.
MetisFL is a tool in the Datasets & Benchmarks category of a tech stack.
Key Features
ScalableOptimized for efficiencySupports synchronous, semi-synchronous and asynchronous protocolsStrong security
MetisFL Pros & Cons
Pros of MetisFL
No pros listed yet.
Cons of MetisFL
No cons listed yet.
MetisFL Alternatives & Comparisons
What are some alternatives to MetisFL?
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.
