Chevron Left
Back to Generative Deep Learning with TensorFlow

Learner Reviews & Feedback for Generative Deep Learning with TensorFlow by DeepLearning.AI

4.9
stars
292 ratings

About the Course

In this course, you will: a) Learn neural style transfer using transfer learning: extract the content of an image (eg. swan), and the style of a painting (eg. cubist or impressionist), and combine the content and style into a new image. b) Build simple AutoEncoders on the familiar MNIST dataset, and more complex deep and convolutional architectures on the Fashion MNIST dataset, understand the difference in results of the DNN and CNN AutoEncoder models, identify ways to de-noise noisy images, and build a CNN AutoEncoder using TensorFlow to output a clean image from a noisy one. c) Explore Variational AutoEncoders (VAEs) to generate entirely new data, and generate anime faces to compare them against reference images. d) Learn about GANs; their invention, properties, architecture, and how they vary from VAEs, understand the function of the generator and the discriminator within the model, the concept of 2 training phases and the role of introduced noise, and build your own GAN that can generate faces. The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture, and gives them the tools to create and train advanced ML models. This Specialization is for early and mid-career software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models....

Top reviews

LV

Mar 17, 2022

Excellent course - Indepth knowledge delivered by one of the top-developers in an engaginand challenging manner. Superb. Would definitely recommend.

LL

Jun 22, 2021

Great Course. It would be better to have Capstone Project and Peer Review Process to prove that we are actually able to apply all these techniques.

Filter by:

1 - 25 of 49 Reviews for Generative Deep Learning with TensorFlow

By Pramit D

Apr 19, 2021

Excellent course. Highly recommended. Please make a separate course on GAN. Use TensorFlow instead of PyTorch

By Sushanth

Oct 21, 2021

The session on VAE's was interesting, If I could make a suggestion, I would add other generative models, such as Deep Belief Nets, and show how the generated data change from DBNs to VAES to GANS with the same dataset. That would give students a better idea of the tradeoffs involved in each of them.

By Tamim-Ul-Haq M

Jan 29, 2021

Outstanding course that deals with complex topics in Deep Learning explained in short yet precise manner and flawlessly executed.

By Francois R

Mar 18, 2021

Excellent course.

I really appreciated to have a quiz and an assignment each week.

Thanks to all the contributors.

By Yap C H

Feb 21, 2021

Clear explanation on all generative methods. However, I find it too short. The course can be longer and include more generative methods.

By Renjith B

May 1, 2021

Really good content covering the surface of lot of advanced topics.

By Ernest W

Nov 25, 2021

The course will give you an introduction to autoencoders, some extension to neural style transfer from Deeplearning specialization and last week was brief introduction to GANs. Everything is well explained and knowledge from assignments may be re-used during your own projects. After the whole specialization you can't say that it didn't give you an opportunity to learn how to use Tensorflow. However, it's focused mostly on image processing so if you dislike this topic - it's not for you.

By Moustafa S

Jan 17, 2021

really great course, it showed how VAE and AutoEncoders work, also touched on the topic of GANs, the best part was applying what's learned during the whole specialization on building difficult and complicated models from scratch.

By Rajendra A

Jul 23, 2021

Sessions, labs and assignment are really very good from advance programming in Tensorflow perspective. Additional or optional sessions on KL divergence, reconstruction loss would have helped learners a lot.

By luis v

Mar 18, 2022

Excellent course - Indepth knowledge delivered by one of the top-developers in an engaginand challenging manner. Superb. Would definitely recommend.

By lonnie

Jun 23, 2021

Great Course. It would be better to have Capstone Project and Peer Review Process to prove that we are actually able to apply all these techniques.

By Rashmi S

Apr 25, 2022

A wonderful course to learn on how we can achieve the output from the input itself using VAE. Thanks for building this course!

By Darwing G

Aug 6, 2023

Amazing Course.

I Loved It

It is very interesting and by the way you obtain the outcomes you can see inmediately your advances!

By Walter N

Nov 24, 2021

Very Instructive! Laurence is a great teacher explaining. I was able to understand CNN / GANS in a unique and smooth way

By Muhammad N S

Sep 21, 2023

Very good course, I learned many new and interesting things from here. The quizzes and labs are quite challenging.

By Om S

Mar 22, 2024

Although the VAE module was a bit difficult, I found this course helpful to refine my deep learning knowledge.

By Nikolay S

Feb 28, 2021

This course was fantastic! Laurence and DeepLearning.ai team did great job. Definitely recommended.

By Pandey V

Aug 19, 2022

excellent course, which gives a very good insight to modeling with advanced tecnhiques!!

By p g

Oct 26, 2023

Great as all other courses in this set of specializations! Thank you!

By Vahid R J

Jul 6, 2024

A very professional course with an excellent instructor.

By 秦时

Apr 3, 2022

the code really help me deeply understand these methods

By 西川 尚之

Jan 21, 2021

This course is very helpful and useful !

By Parma R R

Apr 22, 2022

Good course! recommend it

By Đạt N

Dec 8, 2022

this course is very good.

By Olexander A

Nov 29, 2021

Thanks, amazing course!