[ FreeCourseWeb.com ] Deep Learning: Advanced Computer Vision (GANs, SSD, +More) (Updated 11/2020)



Download More  Courses Visit and Support Us -->> https://FreeCourseWeb.com







MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch

Genre: eLearning | Language: English + .srt | Duration: 119 lectures (15h) | Size: 2.83 GB

VGG, ResNet, Inception, SSD, RetinaNet, Neural Style Transfer, GANs +More in Tensorflow, Keras, and Python

What you'll learn:

Understand and apply transfer learning

Understand and use state-of-the-art convolutional neural nets such as VGG, ResNet and Inception

Understand and use object detection algorithms like SSD

Understand and apply neural style transfer

Understand state-of-the-art computer vision topics

Class Activation Maps

GANs (Generative Adversarial Networks)

Object Localization Implementation Project



Requirements

Know how to build, train, and use a CNN using some library (preferably in Python)

Understand basic theoretical concepts behind convolution and neural networks

Decent Python coding skills, preferably in data science and the Numpy Stack



Description

Latest update: Instead of SSD, I show you how to use RetinaNet, which is better and more modern. I show you both how to use a pretrained model and how to train one yourself with a custom dataset on Google Colab.



This is one of the most exciting courses I’ve done and it really shows how fast and how far deep learning has come over the years.



Use Winrar to Extract. And use a shorter path when extracting, such as C: drive



ALSO ANOTHER TIP: You Can Easily Navigate Using Winrar and Rename the Too Long File/ Folder Name if Needed While You Cannot in Default Windows Explorer. You are Welcome ! :)



Download More  Courses Visit and Support Us -->> https://FreeCourseWeb.com



Get More Tutorials and Support Us -->> https://DevCourseWeb.com



We upload these learning materials for the people from all over the world, who have the talent and motivation to sharpen their skills/ knowledge but do not have the financial support to afford the materials. If you like this content and if you are truly in a position that you can actually buy the materials, then Please, we repeat, Please, Support Authors. They Deserve it! Because always remember, without "Them", you and we won't be here having this conversation. Think about it! Peace...