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Image Super-Resolution GANs

Enhance/upsample images with Generative Adversarial Networks using Python and Tensorflow 2.0
3.6
☆☆☆☆☆ 3.6/5
(6 reviews)
53 students
Created by
Brad Klingensmith

8.3

Classbaze Grade®

9.7

Freshness

6.9

Popularity

7.6

Material

Detailed Analysis »

Enhance/upsample images with Generative Adversarial Networks using Python and Tensorflow 2.0
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Platform: Udemy
Price: check current price
Video: 2h 31m
Language: English
Next start: On Demand

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Classbaze Rating

Classbaze Grade®

8.3 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

9.7 / 10
This course was last updated on 1/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

6.9 / 10
We analyzed factors such as the rating (3.6/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

7.6 / 10
Video Score: 7.9 / 10
The course includes 2h 31m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 4 hours 24 minutes of 10 Generative Adversarial Networks (GAN) courses on Udemy.
Detail Score: 9.3 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 5.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
0 resource.
0 exercise.
0 test.

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About this course

  The course will teach you this
  What you need to START the course
  Who can start this course?
General questions
  Coupons & Discounts
  Guarantees & money back
  Financial aid
Teacher
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About the course

We’ve all seen the gimmick in crime TV shows where the investigators manage to take a tiny patch of an image and magnify it with unrealistic clarity. Well today, Generative Adversarial Networks are making the impossible possible.
Dive into this course where I’ll show you how easily we can take the fundamentals from my High Resolution Generative Adversarial Networks course and build on this to accomplish this impressive feat known as Super-resolution. Not only will you be able to train a Generator to magnify an image to 4 times it’s original size (that’s 16 times the number of pixel!), but it will take relatively little effort on our end.
Just as in the first course, we’ll use Python and TensorFlow 2.0 along with Keras to build and train our convolutional neural networks. And since training our networks will require a ton of computational power, we’ll once again use Google CoLab to connect to a free Cloud TPU. This will allow us to complete the training in just a few days without spending anything on hardware!
If this sounds enticing, take a few minutes to watch the free preview of the “Results!” lesson. I have no doubt that you will come away impressed.

What can you learn from this course?

✓ Create a generator architecture that upsamples an image by 4 times in each dimension
✓ Create a discriminator architecture that scores both realism and fidelity to the original image
✓ Modify custom written Keras layers to accept input images of any size without rebuilding the model
✓ Train the models on a Cloud TPU through Google CoLab
✓ Use the trained generator in a practical application to upsample your own images

What you need to start the course?

• My “High Resolution Generative Adversarial Networks (GANs)” course
• Python experience
• Convolutional neural network experience
• Basic familiarity with TensorFlow 2.0 and Keras

Who is this course is made for?

• Python + TensorFlow 2.0 developers who want to enlarge images with photorealistic detail and clarity

Are there coupons or discounts for Image Super-Resolution GANs ? What is the current price?

The course costs $14.99. And currently there is a 25% discount on the original price of the course, which was $39.99. So you save $25 if you enroll the course now.
The average price is $16.5 of 10 Generative Adversarial Networks (GAN) courses. So this course is 9% cheaper than the average Generative Adversarial Networks (GAN) course on Udemy.

Will I be refunded if I'm not satisfied with the Image Super-Resolution GANs course?

YES, Image Super-Resolution GANs has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any financial aid for this course?

Currently we could not find a scholarship for the Image Super-Resolution GANs course, but there is a $25 discount from the original price ($39.99). So the current price is just $14.99.

Who will teach this course? Can I trust Brad Klingensmith?

Brad Klingensmith has created 2 courses that got 18 reviews which are generally positive. Brad Klingensmith has taught 121 students and received a 3.9 average review out of 18 reviews. Depending on the information available, we think that Brad Klingensmith is an instructor that you can trust.

Learn everything about

Brad Klingensmith

Machine Learning Instructor
I’m a software engineer with a passion for machine learning.

I have over a decade of professional experience developing software for a large corporation but recently decided to dedicate myself full-time to machine learning research. I look forward to learning about exciting new topics, and in turn, teaching them here.

My long-term goal is to help push forward the state of the art in machine learning so that we can one day apply it our world’s greatest problems particularly health and longevity.

I believe in Deep Mind’s mission to “solve intelligence” and then use intelligence “to solve everything else”.
Brad Klingensmith's full profile and courses »
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8.3

Classbaze Grade®

9.7

Freshness

6.9

Popularity

7.6

Material

Detailed Analysis »

Enhance/upsample images with Generative Adversarial Networks using Python and Tensorflow 2.0
Go to course »
Platform: Udemy
Price: check current price
Video: 2h 31m
Language: English
Next start: On Demand

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