As sort of a continuation from my last post, in this tutorial I will demonstrate how to make a basic image detection app using a Tiny YOLOv2 model trained on custom data.
Right now, YOLOv2 is the state-of-the-art object detection system. Trained on the VOC and COCO datasets, it processes images in real-time with high accuracy. If you've ever wanted to train YOLOv2 to detect custom objects, this tutorial will walk you through the process from installation to testing.
According to Abernathy MacGregor, a strategic communications firm, as of 2014, more than 75 percent of trades on US stock exchanges are from automated trading systems. If you've ever wondered how they do it, this notebook and the one it references could serve as a quick introduction.
