Udemy – Deep Learning :Adv. Computer Vision (access stuff + more!) 2020-12 – Download

Explanation

Deep Learning : Adv. Computer Theory (Knowing something + more!), I think what you will find is that, in this course completely different from the previous one, you will be impressed by how much material we can cover. We’ll bridge the gap from the basic CNN architecture you already know and love, to modern, new architectures like ResNet, and Inception. We will understand in detail the components of object detection using both tensorflow object detection api as well as YOLO algorithms. We will look at modern algorithms called RESNET and MobileNetV2 which are both faster and more accurate than their predecessors. One of the best things is that you will understand the fundamentals of CNN and how it transforms object detection into slow motion.

I hope you enjoy learning about these advanced applications of CNNs Yolo and Tensorflow, I’ll see you in class! Instead of focusing on the detailed inner workings of CNNs (which we’ve done before), we’ll focus on the high-level architecture. The result? Almost zero math No complicated low-level coding like that written in Tensorflow, Theano, YOLO, or PyTorch (although optional exercises are included for more advanced students). Most of the course will be in Keras which means a lot of boring, repetitive stuff is written for you.