![Training the Amazon SageMaker object detection model and running it on AWS IoT Greengrass – Part 1 of 3: Preparing training data | The Internet of Things on AWS – Official Blog Training the Amazon SageMaker object detection model and running it on AWS IoT Greengrass – Part 1 of 3: Preparing training data | The Internet of Things on AWS – Official Blog](https://d2908q01vomqb2.cloudfront.net/f6e1126cedebf23e1463aee73f9df08783640400/2020/07/09/instructions-1003x630.png)
Training the Amazon SageMaker object detection model and running it on AWS IoT Greengrass – Part 1 of 3: Preparing training data | The Internet of Things on AWS – Official Blog
![How did I run the official Object Detection API tutorial (`object_detection_tutorial.ipynb`) for TensorFlow in Windows 7? - Dmitry.AI How did I run the official Object Detection API tutorial (`object_detection_tutorial.ipynb`) for TensorFlow in Windows 7? - Dmitry.AI](https://dmitry.ai/uploads/default/original/1X/4bcde8e77cd020acdabc44dd914567862bc7ea04.png)
How did I run the official Object Detection API tutorial (`object_detection_tutorial.ipynb`) for TensorFlow in Windows 7? - Dmitry.AI
GitHub - SrinjaySarkar/Object-Detection-Single-and-multi-object-detection-: This repository contains the Jupyter Notebook for single and multi object detection on the PASCAL VOC dataset.
![Learn Model Inference with OpenVINO™ API in JupyterLab* Environment — OpenVINO™ documentation — Version(2022.3) Learn Model Inference with OpenVINO™ API in JupyterLab* Environment — OpenVINO™ documentation — Version(2022.3)](https://docs.openvino.ai/2022.3/_images/diagram.png)
Learn Model Inference with OpenVINO™ API in JupyterLab* Environment — OpenVINO™ documentation — Version(2022.3)
![Train a 3-D Object Detection Model (Point Pillars) in a Jupyter Notebook | by Anjul Tyagi | Becoming Human: Artificial Intelligence Magazine Train a 3-D Object Detection Model (Point Pillars) in a Jupyter Notebook | by Anjul Tyagi | Becoming Human: Artificial Intelligence Magazine](https://miro.medium.com/v2/resize:fit:348/1*Daxhia6UlQk6hQnkVLxfjw.png)