Our different user roles¶
The AI4OS stack is focused on three different types of users. Depending on what you want to achieve you should belong into one or more of the following categories:
The basic user¶
This user wants to use modules that are already pre-trained and test them with their data. Therefore, they don’t need to have any particular machine learning knowledge. For example, they can take an already trained module for plant classification that has been containerized, and use it to classify their own plant images.
What AI4OS can offer to you:
a Dashboard full of ready-to-use modules to perform inference with your data,
a GUI to easily interact with the services,
an API to integrate the AI modules with your own services,
solutions to run the inference in the Cloud or in your local resources,
the ability to create pipelines by composing different modules.
The intermediate user¶
The intermediate user wants to retrain an available module to perform the same task but fine-tuning it to their own data. They still might not need high level knowledge on modelling of machine learning problems, but typically do need basic programming skills to prepare their own data into the appropriate format. Nevertheless, they can re-use the knowledge being captured in a trained network and adjust the network to their problem at hand by re-training the network on their own dataset. An example could be a user who takes the generic image classifier model and retrains it to perform plant classification.
What AI4OS can offer to you:
the ability to train out-of-the-box a module of the Dashboard,
the ability to easily connect your training to your dataset hosted on our data storage resources,
a private instance of Computer Vision Annotation Tool (CVAT) to annotate your dataset,
a private server to create Federated Learning trainings with Flower,
the ability to use GPUs to accelerate your training,
an API to easily interact with the model,
solutions to deploy your developed model in the Cloud or in your local resources,
the ability to share your module with other users in the Dashboard Marketplace.
Related HowTo’s
The advanced user¶
The advanced users are the ones that will develop their own machine learning models and therefore need to be competent in machine learning. This would be the case for example if we provided an image classification model but the users wanted to perform object localization, which is a fundamentally different task. Therefore they will design their own neural network architecture, potentially re-using parts of the code from other models.
What AI4OS can offer to you:
a ready-to-use IDE (VScode, Jupyterlab) with the main DL frameworks (Pytorch, Tensorflow) running on different types of hardware (CPUs, GPUs),
the ability to easily connect your environment to your dataset hosted on our data storage resources,
the ability to integrate experiment tracking with MLflow in your trainings,
tutorials on performing different types of trainings (incremental learning, distributed learning)
the ability to use GPUs to accelerate your development,
the possibility to integrate your module with the API to enable easier user interaction,
solutions to deploy your developed model in the Cloud or in your local resources,
the ability to share your module with other users in the Dashboard Marketplace.
Related HowTo’s