In this course, you’ll learn the basics of deep learning, and build your own deep neural networks using PyTorch. You’ll get practical experience with PyTorch through coding exercises and projects implementing state-of-the-art AI applications such as style transfer and text generation.
Why Take This Course?
Deep learning is driving the AI revolution and PyTorch is making it easier than ever for anyone to build deep learning applications. In this course, you’ll gain practical experience building and training deep neural networks using PyTorch. You’ll be able to use these skills on your own personal projects.
Dimitrios Tosidis completed this course, spending 2 hours a week on it and found the course difficulty to be medium.
I took the challenge from Facebook. I wish I could have more time, I spent around 23 hours, although I had almost 10 weeks for it. The course is very interesting, as they give a lot of code to experiment with. The several methods need a lot of time and computation power, you have to use a public cloud for AI. The course has the scope of image recognition, but it goes further with text recognition with methods that are developed during the last 4 years, such as convolution neural networks and recurrent neural networks.
Anonymous completed this course.
I completed this course because I waned to apply a Bertelsmann scholarship on Udacity, it's a great course with a pretty useful stuff on PyTorch, very practical with a complete repo on GitHub , 4/5