diff --git a/README.md b/README.md index 2af25e88d..d6f698a88 100644 --- a/README.md +++ b/README.md @@ -28,8 +28,8 @@ ___ ___ :question: **DISCO TECHNOLOGY** -- DISCO supports arbitrary deep learning tasks and model architectures, via [TF.js](https://www.tensorflow.org/js) -- :sparkles: relies on [peer2peer](https://peerjs.com/) communication +- DISCO supports arbitrary deep learning tasks and model architectures in your browser via [TF.js](https://www.tensorflow.org/js) +- Decentralized learning :sparkles: relies on [peer2peer](https://peerjs.com/) communication - Have a look at how DISCO ensures privacy and confidentiality [HERE](docs/PRIVACY.md) ___ @@ -50,16 +50,12 @@ ___ :checkered_flag: **HOW TO USE DISCO** -- Start by exploring our example *DISCOllaboratives* in the [`Tasks` page](https://discolab.ai/#/list). -- The example models are based on popular datasets such as [Titanic](https://www.kaggle.com/c/titanic), [MNIST](https://www.kaggle.com/c/digit-recognizer) or [CIFAR-10](https://www.kaggle.com/pankrzysiu/cifar10-python) -- It is also possible to create your own task without coding on the [custom training page](https://discolab.ai/#/create): +- Start by exploring our examples tasks in the [`DISCOllaboratives` page](https://discolab.ai/#/list). +- The example DISCOllaboratives are based on popular datasets such as [Titanic](https://www.kaggle.com/c/titanic), [MNIST](https://www.kaggle.com/c/digit-recognizer) or [CIFAR-10](https://www.kaggle.com/pankrzysiu/cifar10-python) +- It is also possible to create your own DISCOllaboratives without coding on the [custom training page](https://discolab.ai/#/create): - Upload the initial model - - You can choose from several existing dataloaders - Choose between federated and decentralized for your DISCO training scheme ... connect your data and... done! :bar_chart: - For more details on ML tasks and custom training have a look at [this guide](./docs/TASK.md) - -> **Note**: Currently only `CSV` and `Image` data types are supported. Adding new data types, preprocessing code or dataloaders, is accessible in developer mode (see [developer guide](https://github.com/epfml/disco/blob/develop/DEV.md)). - __ **JOIN US**