Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
5 Hour(s) 54 Minute(s)
Language
English
Taught by
Mustafa Mahrous
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
1 views
Course Overview
A comprehensive course on GANs including state of the art methods, recent techniques, and step-by-step hands-on projects
Master the basic building blocks of modern generative adversarial networks with a unique course that reviews the most recent research papers in GANs and at the same time gives the learner a very detailed hands-on experience in the topic. Start by learning the very basics of how GANs work and incrementally learn more cleverly crafted techniques that enhance your models from the basic GANs towards the more advanced Progressive Growing of GANs. On the journey, you shall learn a fair amount of deep learning concepts with an adequate discussion of the mathematics behind the modern models.
Course Content
- 8 section(s)
- 34 lecture(s)
- Section 1 Course Agenda
- Section 2 Introduction to PyTorch for GANs
- Section 3 Generate Handwritten Digits with Vanilla GAN
- Section 4 Generate Specific Digits with Conditional GAN
- Section 5 Diving Deeper with a Deep Convolutional GAN
- Section 6 Generate Realistic Human Faces with Progressive GAN
- Section 7 Generate Videos from Other Videos
- Section 8 Appendix: Interesting Readings
What You’ll Learn
- How Generative Adversarial Networks work internally
- How to implement state of the art GANs techniques and methods using PyTorch
- How to improve the training stability of GANs
Reviews
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CChris Allen
This course is horrible, Nothing is really explained. They market in the intro video about doing vid2vid but then when you go to the section it doesnt havent any useful information in there at all. Im going to ask for a refund. But DO NOT BUY THIS COURSE. Or accept that you are throwing money away for poorly explained jupyter notebooks that anyone could find
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PPablo Rosales
Would love a bit more detail on what things are, like stride, Max Pool, etc. Maybe that's on another course.
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SSidharth Singla
Not at all good course for learning theory of GANs. Speaker rushes through the content, and have not covered much. Speaker's focus is on code mostly.
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RRaagini Vishnubhotla
A good match, but very hard to understand accent. Please add correct subtitles!
