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Update train-an-ml-capability.md #21

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Update train-an-ml-capability.md
tall-josh Dec 17, 2024
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Update train-an-ml-capability.md
tall-josh Dec 17, 2024
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64 changes: 31 additions & 33 deletions content/docs/how-to-guides/train-an-ml-capability.md
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Expand Up @@ -28,46 +28,44 @@ The steps are as follows:
3. [Configure the training run](#configure-the-training-run): Select the type of model you wish to train and configure it
4. [Schedule training](#schedule-training):
5. [Inspect training metrics](#inspect-training-metrics):
6. [Deploy the capability[(#deploy-the-capability)
6. [Deploy the capability](#deploy-the-capability)

## Create a Capability

1. From the **Develop** tab select **Capabilites/Library** and click **New Capability**
2. Select a **Capability Type**
- `DetectorElement`: Locates and classifies objects within an image using a bounding box or polygon. ie: *Locates all cats and dogs in images and classifies the as cat or dog*
- `BoxClassifierElement`: Performs classification on regions of an image. Typically downstream of a `DetectorElement`. ie: *Given a collection of cat regions produced by the above cat/dog `DetectorElement`, classify if the cat is evil or not*
- `BoxEmbedderElement`: Similar to `BoxClassifierElement` but returns embeddings for the regions rather than classifications
- `DetectorElement`: Locates and classifies objects within an image using a bounding box or polygon. ie: *Locates all cats and dogs in images and classifies the as cat or dog*
- `BoxClassifierElement`: Performs classification on regions of an image. Typically downstream of a `DetectorElement`. ie: *Given a collection of cat regions produced by the above cat/dog `DetectorElement`, classify if the cat is evil or not*
- `BoxEmbedderElement`: Similar to `BoxClassifierElement` but returns embeddings for the regions rather than classifications
3. Give it a name and description
4. Refer to below for information on each tab:
- `DetectorElement`:
- **Interface**:
- **inputs**: image
- **outputs**: entities
- **Parameters**:
- ToDo
- **Model Parameters**:
- All *Head* set to "0" for now
- Add each output of your capability to a different *Position*. Must start at 0 and increment by 1

- `BoxClassifierElement`:
- **Interface**:
- **inputs**: image, entities
- **outputs**: entities
- **Parameters**:
- ToDo
- **Model Parameters**:
- All *Head* set to "0" for now
- Add each output of your capability to a different *Position*. Must start at 0 and increment by 1

- `BoxEmbedderElement`:
- **Interface**:
- **inputs**: image, entities
- **outputs**: entities
- **Parameters**:
- ToDo
- **Model Parameters**:
- All *Head* set to "0" for now
- Add each output of your capability to a different *Position*. Must start at 0 and increment by 1
- `DetectorElement`:
- **Interface**:
- **inputs**: image
- **outputs**: entities
- **Parameters**:
- ToDo
- **Model Parameters**:
- All *Head* set to "0" for now
- Add each output of your capability to a different *Position*. Must start at 0 and increment by 1
- `BoxClassifierElement`:
- **Interface**:
- **inputs**: image, entities
- **outputs**: entities
- **Parameters**:
- ToDo
- **Model Parameters**:
- All *Head* set to "0" for now
- Add each output of your capability to a different *Position*. Must start at 0 and increment by 1
- `BoxEmbedderElement`:
- **Interface**:
- **inputs**: image, entities
- **outputs**: entities
- **Parameters**:
- ToDo
- **Model Parameters**:
- All *Head* set to "0" for now
- Add each output of your capability to a different *Position*. Must start at 0 and increment by 1


## Create datasets
Expand Down