add label_data table of contents nb

label_data/index.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Ground Truth\n",
+    "\n",
+    "Amazon SageMaker Ground Truth is a fully managed data labeling service that makes it easy to build highly accurate training datasets for machine learning."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Get started with Ground Truth\n",
+    "\n",
+    "[This video](https://www.youtube.com/embed/_FPI6KjDlCI) shows you how to setup and use Amazon SageMaker Ground Truth. (Length: 9:37)\n",
+    "\n",
+    "### End-to-end demo: from unlabeled data to a deployed ML model\n",
+    "\n",
+    "[From Unlabeled Data to a Deployed Machine Learning Model: A SageMaker Ground Truth Demonstration for Image Classification](../ground_truth_labeling_jobs/from_unlabeled_data_to_deployed_machine_learning_model_ground_truth_demo_image_classification/from_unlabeled_data_to_deployed_machine_learning_model_ground_truth_demo_image_classification.ipynb)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Task types\n",
+    "\n",
+    "### 3D point clouds\n",
+    "* [Create a 3D Point Cloud Labeling Job with Amazon SageMaker Ground Truth](../ground_truth_labeling_jobs/3d_point_cloud_demo/create-3D-pointcloud-labeling-job.ipynb)\n",
+    "* [Create a 3D Point Cloud Labeling Job for Object Tracking with Amazon SageMaker Ground Truth](../ground_truth_labeling_jobs/3d_point_cloud_input_data_processing/3D-point-cloud-input-data-processing.ipynb)   \n",
+    "\n",
+    "\n",
+    "### Annotation consolidation\n",
+    "* [Understanding Annotation Consolidation: A SageMaker Ground Truth Demonstration for Image Classification](../ground_truth_labeling_jobs/annotation_consolidation/ACSBlogPost.ipynb)\n",
+    "\n",
+    "\n",
+    "### Object detection\n",
+    "* [From Unlabeled Data to a Deployed Machine Learning Model: A SageMaker Ground Truth Demonstration for Object Detection](../ground_truth_labeling_jobs/ground_truth_object_detection_tutorial/object_detection_tutorial.ipynb)\n",
+    "\n",
+    "\n",
+    "### Pretrained model labeling\n",
+    "* [Using a Pre-Trained Model for Cost Effective Data Labeling](../ground_truth_labeling_jobs/pretrained_model/pretrained_model_labeling_tutorial.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Bring your own model\n",
+    "\n",
+    "* [Create an Active Learning Workflow using Amazon SageMaker Ground Truth](../ground_truth_labeling_jobs/bring_your_own_model_for_sagemaker_labeling_workflows_with_active_learning/bring_your_own_model_for_sagemaker_labeling_workflows_with_active_learning.ipynb)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Analysis tasks\n",
+    "\n",
+    "### Data analysis of image classification\n",
+    "* [Data Analysis Using a Ground Truth Image Classification Output Manifest](../ground_truth_labeling_jobs/data_analysis_of_ground_truth_image_classification_output/data_analysis_of_ground_truth_image_classification_output.ipynb)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "instance_type": "ml.t3.medium",
+  "kernelspec": {
+   "display_name": "Python 3 (Data Science)",
+   "language": "python",
+   "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-west-2:236514542706:image/datascience-1.0"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}