diff --git a/config.toml b/config.toml index b279b4f..c54896b 100644 --- a/config.toml +++ b/config.toml @@ -1408,12 +1408,19 @@ theme = "doc-theme" parent = "pybytes" weight = 80 - [[menu.main]] - name = "Pymesh Integration" - url = "/pybytes/pymeshintegration/" - identifier = "pybytes@pymeshintegration" - parent = "pybytes" - weight = 90 +[[menu.main]] + name = "Pymesh Integration" + url = "/pybytes/pymeshintegration/" + identifier = "pybytes@pymeshintegration" + parent = "pybytes" + weight = 90 + +[[menu.main]] + name = "Machine Learning" + url = "/pybytes/mlintegration/" + identifier = "pybytes@mlintegration" + parent = "pybytes" + weight = 100 [[menu.main]] name = "Amazon IoT" diff --git a/content/pybytes/mlintegration/_index.md b/content/pybytes/mlintegration/_index.md new file mode 100644 index 0000000..81c6183 --- /dev/null +++ b/content/pybytes/mlintegration/_index.md @@ -0,0 +1,16 @@ +--- +title: "Machine Learning Integration" +aliases: +--- + +## What does Machine Learning integration offer you? + +This documentation is a quick introduction to the new Machine Learning integration features on Pybytes. + +The Machine Learning integration is here to help you to create smart machine learning models using Pycom devices. + +## Let's get started! + +* [Machine Learning Model Creation](/pybytes/mlintegration/modelcreation) + +* [Machine Learning Features](/pybytes/mlintegration/features) diff --git a/content/pybytes/mlintegration/features.md b/content/pybytes/mlintegration/features.md new file mode 100644 index 0000000..816202e --- /dev/null +++ b/content/pybytes/mlintegration/features.md @@ -0,0 +1,65 @@ +## Model Features + +### Data Acquisition + +#### Create Sample + +In the data acquisition module the samples for training can be collected. + +After setting all sample parameters in the form click on **Create Sample** to start. + +The sampling occurs when the device led is amber, when the light turns purple, the device is processing and saving the samples. + +If the device gets stuck showing the purple light, maybe the sampling should be done again. + +#### Data Collection + +The data collection shows the collected samples. Click on the sample to see the graph. + +![Data Acquisition](/gitbook/assets/pybytes/ml/data_acquisition_graph.png) + +### Processing + +#### Raw Data + +In the processing tab, the Windows Size and Windows Step should be filled. Select the data range on the graph to fill the Windows step. + +#### Spectral Analysis + +After selecting the data range to be analyzed. Fill the form and click in the button **Process Signal** + +![Processing](/gitbook/assets/pybytes/ml/processing.png) + +#### Training + +Fill the Neural Network Settings form and click on **START TRAINING** to train the model. + +The results can be checked on the Training Performance section. + +![Training](/gitbook/assets/pybytes/ml/training.png) + +#### Testing + +In the module, the samples for testing can be collected. + +After setting all sample parameters in the form click on **Create Sample** to start. + +#### Data Collection + +The data collection shows the testing collected samples. Click on the **Test xxx Samples** to test the module. + +![Testing](/gitbook/assets/pybytes/ml/testing.png) + +After the testing is performed, the results can be checked below the Data collection form. + +![Testing Results](/gitbook/assets/pybytes/ml/testing_results.png) + +#### Model Deployment + +After all training and testing, the model can be deployed into the devices. + +Select the devices and click on the **DEPLOY MODEL** button. + +![Model Deployment](/gitbook/assets/pybytes/ml/deploy.png) + +[**Machine Learning Integration**](/pybytes/mlintegration) diff --git a/content/pybytes/mlintegration/modelcreation.md b/content/pybytes/mlintegration/modelcreation.md new file mode 100644 index 0000000..060849b --- /dev/null +++ b/content/pybytes/mlintegration/modelcreation.md @@ -0,0 +1,42 @@ +## Model Creation + +The first step to use the machine learning feature on Pybytes is the model creation. + +The Machine Learning app can be accessed in the main sidebar. + +![Machine Learning App](/gitbook/assets/pybytes/ml/pybytes_front_page.png) + + +To create a new model, click on **ADD MODEL** button and follow the wizard. + +The existing models are listed below. + +![Create Model](/gitbook/assets/pybytes/ml/ml_page.png) + +### Model Wizard + +#### The first step is the model definition. + +In the model definition the fields **Name**, **Description**, and **Sample frequency** should be fulfilled. + +![Model Definition](/gitbook/assets/pybytes/ml/model_definition.png) + +#### The second step is the model configuration. + +In the model configuration, the processing block type and learning block technique should be selected. + +In the beta version, only the Spectral Analysis (processing block type) and Neural Network (learning block technique) are available. + +![Model Configuration](/gitbook/assets/pybytes/ml/model_config.png) + +#### The third step is the Device Selection. + +In the third step the devices that will be used to train and test the model should be selected. + +![Device Selection](/gitbook/assets/pybytes/ml/select_device.png) + +And now the model is ready to be used! 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