Fixed API page and some headings

docs/apiclient.rst

@@ -39,7 +39,7 @@ Then passing a token as an argument is not required.
    >>> from fedn import APIClient
    >>> client = APIClient(host="<controller-host>", secure=True, verify=True)
 
-**Set the active package and seed model**
+**Set the active compute package and seed model**
 
 To set the active compute package in the FEDn Studio Project:
 
@@ -52,13 +52,8 @@ To set the active compute package in the FEDn Studio Project:
 
 **Start a training session**
 
-Once the active package and seed model are set, you can connect clients to the network and start training models. The following code snippet starts a traing session:
-
-.. code-block:: python
-   
-   session = client.start_session(id="session_name")
-
-**Run training sessions using the Python APIClient**
+Once the active package and seed model are set, you can connect clients to the network and start training models. To run a training session
+using the default aggregator (FedAvg):
 
 .. code:: python
 
@@ -72,17 +67,38 @@ Once the active package and seed model are set, you can connect clients to the n
    >>> model_id = models[-1]['model']
    >>> validations = client.get_validations(model_id=model_id)
 
-**Accessing global models**
+To run a session using the FedAdam aggregator using custom hyperparamters: 
+
+.. code-block:: python
+
+   >>> session_id = "experiment_fedadam"
 
-You can also access global model updates via the APIClient:
+   >>> session_config = {
+                     "helper": "numpyhelper",
+                     "id": session_id,
+                     "aggregator": "fedopt",
+                     "aggregator_kwargs": {
+                           "serveropt": "adam",
+                           "learning_rate": 1e-2,
+                           "beta1": 0.9,
+                           "beta2": 0.99,
+                           "tau": 1e-4
+                           },
+                     "model_id": seed_model['model'],
+                     "rounds": 10
+                  }
+
+   >>> result_fedadam = client.start_session(**session_config)
+
+**Download a global model**
+
+To download a global model and write it to file:
 
 .. code:: python
 
    >>> ...
    >>> client.download_model("<model-id>", path="model.npz")
 
-Please see :py:mod:`fedn.network.api` for more details on how to use the APIClient. 
-
 **List data**
 
 Other than starting training sessions, the APIClient can be used to get data from the network, such as sessions, models etc. All entities are represented and they all work in a similar fashion.
@@ -101,17 +117,17 @@ Entities represented in the APIClient are:
 * statuses
 * validations
 
-The following code snippet shows how to list all sessions:
-
+To list all sessions: 
 .. code-block:: python
    
-   sessions = client.get_sessions()
+   >>> sessions = client.get_sessions()
 
-And the following code snippet shows how to get a specific session:
+To get a specific session:
 
 .. code-block:: python
    
-   session = client.get_session(id="session_name")
-
+   >>> session = client.get_session(id="session_name")
 
-For more information on how to use the APIClient, see the :py:mod:`fedn.network.api.client`, and the example `Notebooks <https://github.com/scaleoutsystems/fedn/tree/master/examples/notebooks>`_. 
+For more information on how to use the APIClient, see the :py:mod:`fedn.network.api.client`, and the collection of example Jupyter Notebooks:
+
+- `API Example <https://github.com/scaleoutsystems/fedn/tree/master/examples/notebooks>`_  . 

docs/developer.rst

@@ -1,7 +1,12 @@
 .. _developer-label:
 
-Local development sandbox
-=========================
+================
+Developer guide
+================
+
+
+Pseudo-distributed sandbox
+===========================
 
 .. note::
    These instructions are for users wanting to set up a bare-minimum local deployment of FEDn (without FEDn Studio).

docs/helpers.rst

@@ -1,6 +1,6 @@
 .. _helper-label:
 
-Model Serialization/Deserialization
+Model marshalling
 ===================================
 
 In federated learning, model updates need to be serialized and deserialized in order to be 

docs/introduction.rst

@@ -13,10 +13,11 @@ The server aggregates and combines the gradients from multiple participants to u
 This iterative process allows the global model to improve without the need to share the raw data.
 
 
-FEDn: An enterprise-ready federated learning framework 
--------------------------------------------------------
+The FEDn framework 
+--------------------
 
-Our goal is to provide a federated learning framework that is both secure, scalable and easy-to-use. We believe that that minimal code change should be needed to progress from early proof-of-concepts to production. This is reflected in our core design: 
+The goal with FEDn is to provide a federated learning framework that is secure, scalable and easy-to-use. Our ambition is that FEDn supports the full journey from early
+testing/exploration, through pilot projects, to real-world depoyments and integration. We believe that that minimal code change should be needed to progress from early proof-of-concepts to production. This is reflected in our core design: 
 
 -  **Minimal server-side complexity for the end-user**. Running a proper distributed FL deployment is hard. With FEDn Studio we seek to handle all server-side complexity and provide a UI, REST API and a Python interface to help users manage FL experiments and track metrics in real time.
 
@@ -66,4 +67,4 @@ Support
 Community support in available in our `Discord
 server <https://discord.gg/KMg4VwszAd>`__.
 
-Options are available for `Enterprise support <https://www.scaleoutsystems.com/start#pricing>`__.
+For professionals / Enteprise, we offer `Dedicated support <https://www.scaleoutsystems.com/start#pricing>`__.