Learn ML

Object detection is a key task in Computer Vision. It has a great history of development, back from times when computers were too heavy to carry them around. Object Detection is an evolutional step for a wide range of applications such as military applications, urban planning, and environmental management. Nevertheless, it's a challenging task due to the different scales and appearances of the objects.

This course was designed as a next step of learning for people who already got basic knowledge from Coursera, Udemy, edX, etc and for people who want to expand their expertise in another area of Machine Learning. We are bridging the gap between theory and practical knowledge so you will be ready for real-life projects, master computer vision, and image processing and get a better job within months of the course completion.

It is created by developers to developers and provides a deep understanding of the object detection tasks in the computer vision field. Topics of the course will guide you through the path of developing modern object detection algorithms and models, so you will learn to apply deep learning architectures to computer vision tasks. Discover how to proceed in researching this area and create a more accurate solution. Topics of the course include simple localization models (based on coordinates and mask), single shoot networks (Yolo, SSD) and regional proposal networks (Faster RCNN, Mask RCNN).