Chevron Left
Вернуться к Generative Deep Learning with TensorFlow

Отзывы учащихся о курсе Generative Deep Learning with TensorFlow от партнера deeplearning.ai

4.8
звезд
Оценки: 176
Рецензии: 28

О курсе

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....

Лучшие рецензии

LV

17 мар. 2022 г.

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

LL

22 июня 2021 г.

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.

Фильтр по:

1–25 из 29 отзывов о курсе Generative Deep Learning with TensorFlow

автор: Tamim-Ul-Haq M

29 янв. 2021 г.

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

автор: Francois R

18 мар. 2021 г.

Excellent course.

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

Thanks to all the contributors.

автор: Yap C H

21 февр. 2021 г.

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

автор: Renjith B

1 мая 2021 г.

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

автор: Ernest W

25 нояб. 2021 г.

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.

автор: Moustafa S

17 янв. 2021 г.

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.

автор: Rajendra A

23 июля 2021 г.

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.

автор: luis v

18 мар. 2022 г.

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

автор: lonnie

23 июня 2021 г.

G​reat 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.

автор: Rashmi S

25 апр. 2022 г.

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

автор: Walter A N

24 нояб. 2021 г.

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

автор: Pramit D

19 апр. 2021 г.

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

автор: Nikolay S

28 февр. 2021 г.

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

автор: 秦时

3 апр. 2022 г.

the code really help me deeply understand these methods

автор: 西川 尚之

21 янв. 2021 г.

This course is very helpful and useful !

автор: Parma R R

22 апр. 2022 г.

G​ood course! recommend it

автор: Alexander A

29 нояб. 2021 г.

Thanks, amazing course!

автор: Socrates M

2 мар. 2021 г.

Amazing course indeed!

автор: Jorge S

29 мар. 2021 г.

Best content around !

автор: Alexander Z

22 мар. 2021 г.

Great course. Thanks!

автор: Shiva S B

16 авг. 2021 г.

useful material

автор: Merlin S

9 июля 2021 г.

L​ovely course.

автор: Vikum C

2 июня 2021 г.

great course

автор: Javier B

6 июля 2021 г.

very nice

автор: tom g

25 июня 2021 г.

Amazing