Deep Learning CNN Convolutional Neural Networks with Python - YOLO Algorithm

The video tutorial discusses the application of object detection in real-world problems using YOLO. It explains the process of dividing images into bounding boxes and classes, designing target labels, and using convolutional neural networks for training and testing. The tutorial also addresses challenges like multiple detections of the same object and introduces non-maximum suppression as a solution.

What are the different classes of objects that YOLO can detect, and how are they represented?

How does the structure of the data set affect the performance of the YOLO model?

What is non-maximum suppression and why is it important in object detection?