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Stadle, A platform for federated learning.

Project description

STADLE v0.0.2

Our STADLE platform is a paradigm-shifting technology for collaborative and continuous learning combining privacy-preserving frameworks. STADLE platform stands for Scalable, Traceable, Adaptive, Distributed Learning platform for versatile ML applications.

Table of Contents

General Terminologies

There are 3 main components in STADLE.

  • Persistence-server

    • A core functionality which helps in keeping track of various database entries.
    • Packaged as a command inside stadle library.
    • stadle persistence-server [args]
  • Aggregator

    • A core functionality which helps aggregation process.
    • Packaged as a command inside stadle library.
      • stadle aggregator [args]
  • Client [this package]

    • In charge of communicating with stadle core functions.
    • A core functionality which helps executing the machine learning code from client side.
    • Packaged inside stadle library as a class.
      • from stadle import BasicClient
      • class BasicClient is used to let stadle know that the following code is going to be ML oriented.

Contributing

Reach out with your issues or proposals to improve STADLE.

Bug Reports

Please check/submit issues here.

Tech Support

Please reach out to our technical support team via support@tie-set.com.

License

Any use and distribution of this code must be under the NDA with TieSet Inc.

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