Generative Adversarial Network (GANs) Full Coding Example Tutorial in Tensorflow 2.0!

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I'm going to build a generative adversarial network from scratch and explain each step as I go through it! Follow and learn how to build such networks yourself!

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Never really thought I could grasp GANs in half an hour! Concise and clear! Just, ... WOW! Please don't stop making videos like this. Thank you!

_adi_
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YouTube recommendation systems got better I guess, for making me land on this beautiful tutorial. Thanks a lot for this!!!

harishlakshmanapathi
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this must be one of the best GAN videos on Youtube!

danielmartin
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Lot of videos on pytorch
Finally a worthy video on tensorflow
Thank you mate♥️

bornnoob
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I liked it very much! It was really helpful for me! Thanks a lot. I did not know that I can get the idea of how GANs are working in just half an hour! Awesome! Please keep making these types of videos! !

salarghaffarian
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Best video to learn GANs ever and for free. I love it. Thank's!

wellwell
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So helpful. Thank you. Never stop making these videos.

eunjulee
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Finally, Youtube is making good suggestions

AhmedIsam
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Thanks for sharing. Hope for more on this topic. Great work

DanielWeikert
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please explain small bits about the functions you are using during the silence..

tna_
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When I start training I am getting an error: input must be 4-dimensional[100, 100] [Op:Conv2D] any solutions?

maulenabdakov
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Hi,
please which method of Deep Learning fits with the dynamic environment big data size, as like massive data connectivity in wireless communication, and we have milimeterwave beamforming massive multi-input-multi-output devices in a dynamic environment.
Which one of these methods will be fit to solve high computational complexity, to get maximum policy value, perfect beamforming vector, or perfect decision-maker?
Can use GAN, DDPG, Policy Search method?
which of DL methods GAN, DDPG, Policy Search method fits with the Dynamic environment?
Thank you in advanced

Alaaedi

hussainalaaedi
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Thanks for the great video! To the point and clear.

aaronshed
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can you please explain how the normalization technique you applied is going to affect

radhakrishnanrayaprolu
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Please try to develop gans for synthetic data generation

allankimanikanta
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cannot compute Pack as input #1(zero-based) was expected to be a float tensor but is a uint8 tensor [Op:Pack] name: x

kouassialloukoffifranck
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Could you please upload a video on implementation of DCGAN using insert dataset from google drive

lalithavanik
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Hey, Aviv. Question about generator. What exactly could be the problem with the input shape of a generator. The 100 is an arbitrary number - no? I'm getting a ''Can't convert Python sequence with out-of-range integer to Tensor.'' error . Would love a reply and or an e-mail if you have the time. Video was fantastic though - learned a lot.

matisszimerts
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Hello
I'm new in this GAN, i need Help to generate fake OCT image please

Thank you

Dianbarry
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@Aviv Elbag please make the same kind of video about TimeGAN

zainabkhan
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