Computer Vision with Deep Learning

Stay up–to–date with the leading–edge in the Machine Learning and develop an industry portfolio through this course by learning Computer Vision and Deep Learning foundational concepts, Object Detection, Image Classification and Object Tracking.

The recent innovations of Machine Learning technology have brought in huge technological transformation and most of the business are now shifting towards technology–enabled business models fueled by Deep Learning and Computer Vision. To maintain competitiveness in the industry, it is very important to stay up to date and build expertise on these skills.

The course has been designed to empower you with the core concepts of Computer Vision and Deep Learning with neural network, ANN, CNN along with activation function. After covering these basics, the course explains in detail the object detection architecture, illustrates how it is different from object tracking and then details out the widely used object detection models as they have evolved over time. To begin with, we start with the architecture design of R–CNN Model and then move on to FAST R–CNN Model which is advanced version of R–CNN. Thereafter, we explain the concept of Region Proposal Network (RPN) and then leverage it to build FASTER R–CNN MODEL and close this legacy with R–FCN Model. Moving on, the course dives deep into advanced object detection models starting with Retinanet, SSD and then covering the YOLO series in which we are talking about YOLO V3, YOLO V3 Tiny and YOLOV4 Model.