Add toc for v1 doc

Author: PhaniShekhar

articles/machine-learning/v1/toc.yml

@@ -4,11 +4,11 @@
   href: ../index.yml
 - name: Overview (v1)
   items:
-  - name: Architecture & terms 
+  - name: Architecture & terms
     displayName: architecture, concepts, definitions, glossary
     href: concept-azure-machine-learning-architecture.md
   - name: Migrate from ML Studio (classic)
-    items: 
+    items:
     - name: Migration overview
       href: ../migrate-overview.md
     - name: Migrate datasets
@@ -24,11 +24,11 @@
 - name: Concepts (v1)
   items:
   - name: Work with data
-    items: 
+    items:
     - name: Data access
       href: concept-data.md
     - name: Studio network data access
-      href: concept-network-data-access.md      
+      href: concept-network-data-access.md
   - name: Automated ML overview
     displayName: automl, auto ml
     href: concept-automated-ml-v1.md
@@ -47,7 +47,7 @@
   items:
     - name: Python get started (Day 1)
       expanded: true
-      items: 
+      items:
         - name: 1. Run a Python script
           href: tutorial-1st-experiment-hello-world.md
         - name: 2. Train your model
@@ -57,7 +57,7 @@
     - name: "Build a training pipeline (Python)"
       href: "tutorial-pipeline-python-sdk.md"
 - name: Samples (v1)
-  items: 
+  items:
     - name: Jupyter Notebooks
       displayName: example, examples, server, jupyter, azure notebooks, python, notebook, github
       href: samples-notebooks-v1.md
@@ -101,7 +101,7 @@
   - name: Work with data
     items:
     - name: Access data
-      items: 
+      items:
       - name: Connect to Azure storage with datastores
         displayName: blob, get, fileshare, access, mount, download, data lake, datastore
         href: how-to-access-data.md
@@ -129,7 +129,7 @@
         displayName: data, labels, torchvision
         href: how-to-use-labeled-dataset.md
     - name: Get & prepare data
-      items: 
+      items:
       - name: Data ingestion with Azure Data Factory
         displayName: data, ingestion, adf
         href: how-to-data-ingest-adf.md
@@ -143,12 +143,12 @@
         displayName: designer, data, import, dataset, datastore
         href: how-to-designer-import-data.md
     - name: Compliance
-      items: 
+      items:
       - name: Export and delete data
         displayName: GDPR
         href: how-to-export-delete-data.md
   - name: Train models
-    items: 
+    items:
     - name: Configure & submit training run
       displayName: run config, script run config, scriptrunconfig, compute target, dsvm, Data Science Virtual Machine, local, cluster, ACI, container instance, Databricks, data lake, lake, HDI, HDInsight
       href: how-to-set-up-training-targets.md
@@ -172,12 +172,15 @@
       - name: Set up AutoML to train computer vision models with Python
         displayName: auto ML, automl, SDK
         href: how-to-auto-train-image-models-v1.md
+      - name: Auto-train a small object detection model
+        displayName: computer vision, image, image model
+        href: how-to-use-automl-small-object-detect-v1.md
       - name: Local inference using ONNX
         displayName: SDK, automl
         href: how-to-inference-onnx-automl-image-models-v1.md
-    - name: Track experiments with MLflow 
+    - name: Track experiments with MLflow
       displayName: log, monitor, metrics, model registry, register
-      href: how-to-use-mlflow.md  
+      href: how-to-use-mlflow.md
     - name: Log & view metrics
       href: how-to-log-view-metrics.md
     - name: Interpret ML models
@@ -211,7 +214,7 @@
       displayName: update hot reload model mounting
       href: how-to-deploy-update-web-service.md
     - name: Deployment targets
-      items: 
+      items:
         - name: Deploy locally
           href: how-to-deploy-local.md
         - name: Deploy locally on compute instance
@@ -238,15 +241,15 @@
       displayName: swagger inference schema binary cors
       href: how-to-deploy-advanced-entry-script.md
     - name: Prebuilt Docker images
-      items: 
+      items:
         - name: Python extensibility
           href: how-to-prebuilt-docker-images-inference-python-extensibility.md
         - name: Dockerfile extensibility
           href: how-to-extend-prebuilt-docker-image-inference.md
         - name: Troubleshoot prebuilt docker images
           href: how-to-troubleshoot-prebuilt-docker-image-inference.md
     - name: Monitor web services
-      items: 
+      items:
         - name: Collect & evaluate model data
           displayName: track production
           href: how-to-enable-data-collection.md
@@ -262,7 +265,7 @@
     items:
       - name: Build & use ML pipelines
         displayName: pipelines
-        items: 
+        items:
           - name: Create ML pipelines (Python)
             href: how-to-create-machine-learning-pipelines.md
           - name: Moving data into and between ML pipeline steps (Python)
@@ -276,13 +279,13 @@
             href: how-to-use-synapsesparkstep.md
           - name: Trigger a pipeline
             href: how-to-trigger-published-pipeline.md
-      - name: Convert notebook code into Python scripts 
+      - name: Convert notebook code into Python scripts
         displayName: mlops, mlopspython, production
         href: how-to-convert-ml-experiment-to-production.md
 - name: Troubleshoot & debug (v1)
-  items: 
+  items:
     - name: Pipeline issues
-      items: 
+      items:
         - name: Troubleshoot pipelines
           displayName: designer
           href: how-to-debug-pipelines.md
@@ -292,6 +295,6 @@
           displayName: debug_batch consume pipeline parallelrunstep inference
           href: how-to-debug-parallel-run-step.md
 - name: Reference (v1)
-  items: 
+  items:
   - name: Machine learning CLI pipeline YAML reference
     href: reference-pipeline-yaml.md