diff --git a/docs/aggregators.rst b/docs/aggregators.rst index dba34b6b4..5c0e30aa7 100644 --- a/docs/aggregators.rst +++ b/docs/aggregators.rst @@ -116,5 +116,5 @@ This extension can then simply be called as such: .. meta:: :description lang=en: - Aggregators are responsible for combining client model updates into a combiner-level global model. During a training session, the combiners will instantiate an Aggregator and use it to process the incoming model updates from clients. + Aggregators are responsible for combining client model updates into a combiner-level global model. :keywords: Federated Learning, Aggregators, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems diff --git a/docs/apiclient.rst b/docs/apiclient.rst index e0416150c..360691d18 100644 --- a/docs/apiclient.rst +++ b/docs/apiclient.rst @@ -137,6 +137,6 @@ For more information on how to use the APIClient, see the :py:mod:`fedn.network. .. meta:: :description lang=en: - FEDn comes with an APIClient - a Python3 library that can be used to interact with FEDn programmatically. In this tutorial we show how to use the APIClient to initialize the server-side with the compute package and seed models, run and control training sessions and to retrieve models and metrics. + FEDn comes with an APIClient - a Python3 library that can be used to interact with FEDn programmatically. :keywords: Federated Learning, APIClient, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems diff --git a/docs/architecture.rst b/docs/architecture.rst index 4eabe3585..df6f4a2fc 100644 --- a/docs/architecture.rst +++ b/docs/architecture.rst @@ -54,6 +54,6 @@ many different possible outcomes can be achieved. Good starting configurations a .. meta:: :description lang=en: - Architecture overview - Constructing a federated model with FEDn amounts to a) specifying the details of the client-side training code and data integrations, and b) deploying the federated network. + Architecture overview - An overview of the FEDn federated learning platform architecture. :keywords: Federated Learning, Architecture, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems diff --git a/docs/developer.rst b/docs/developer.rst index 697649442..cd55a596b 100644 --- a/docs/developer.rst +++ b/docs/developer.rst @@ -267,6 +267,6 @@ You can use `--token` flags in the FEDn CLI to set the access token. .. meta:: :description lang=en: - During development on FEDn, and when working on own extentions including aggregators and helpers, it is useful to have a local development setup of the core FEDn server-side services (controller, combiner etc). We provide Dockerfiles and docker-compose template for an all-in-one local sandbox + During development on FEDn, and when working on own extentions including aggregators and helpers, it is useful to have a local development setup. :keywords: Federated Learning, Developer guide, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems \ No newline at end of file diff --git a/docs/faq.rst b/docs/faq.rst index 7a27bbcd0..0381aa1a3 100644 --- a/docs/faq.rst +++ b/docs/faq.rst @@ -89,6 +89,6 @@ with the Scaleout team. .. meta:: :description lang=en: - How do you approach the question of output privacy? We take security in (federated) machine learning seriously. Federated learning is a foundational technology that improves input privacy in machine learning by allowing datasets to stay local and private, and not copied to a server. + How do you approach the question of output privacy? We take security in (federated) machine learning seriously. :keywords: Federated Learning, FAQ, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems diff --git a/docs/helpers.rst b/docs/helpers.rst index 4b33d2d5e..1d718c576 100644 --- a/docs/helpers.rst +++ b/docs/helpers.rst @@ -30,6 +30,6 @@ for further details. .. meta:: :description lang=en: - Model marshalling - In federated learning, model updates need to be serialized and deserialized in order to be transferred between clients and server/combiner. There is also a need to write and load models to/from disk, for example to transiently store updates during training rounds. + In federated learning, model updates need to be serialized and deserialized in order to be transferred between clients and server/combiner. :keywords: Federated Learning, Model marshalling, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems diff --git a/docs/index.rst b/docs/index.rst index eb8af4def..7362a42bc 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -32,6 +32,6 @@ Indices and tables .. meta:: :description lang=en: - FEDn is a federated learning platform that is secure, scalable and easy-to-use. FEDn supports the full journey from early testing/exploration, through pilot projects, to real-world deployments and integration. + FEDn is a federated learning platform that is secure, scalable and easy-to-use. :keywords: Federated Learning, Machine Learning, Federated Learning Framework, Federated Learning Platform, FEDn, Scaleout Systems \ No newline at end of file diff --git a/docs/introduction.rst b/docs/introduction.rst index 15694dc24..13a3d8fde 100644 --- a/docs/introduction.rst +++ b/docs/introduction.rst @@ -84,7 +84,7 @@ For professionals / Enteprise, we offer `Dedicated support