A Friendly Introduction to Generative Adversarial Networks (GANs)
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- เผยแพร่เมื่อ 4 พ.ค. 2020
- Code: www.github.com/luisguiserrano/...
What is the simplest pair of GANs one can build? In this video (with code included) we build a pair of ONE-layer GANs which will generate some simple 2x2 images (faces).
Grokking Machine Learning Book: www.manning.com/books/grokkin...
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GANs from Scratch 1: A deep introduction. With code in PyTorch and TensorFlow: / gans-from-scratch-1-a-... - วิทยาศาสตร์และเทคโนโลยี
As a beginner in ML a lot of this still went over my head but it's the most accessible video I've found yet on GANs! Thank you so much
You sir are a fantastic teacher. No fancy gimmicks, no catch phrases. Just pure talent. Hoping to collaborate with you!
getting to see this after a heavy day at work is refreshing..
Thank you so much for sharing
This is one of the best explanations I have ever seen. You manage to cover the goal and the method intuitively, mathematically, and programmatically, and you did it with a concrete example that was simple enough to work out by hand. I also appreciate that you showed how we might code the rules for a solution, and then showed how are would program a machine learning approach to come up with a similar solution. I hope you continue to make more excellent videos like this!
This channel’s been a gem of a find, always a go to source to refresh seemingly complex algorithms in an absurdly intuitive way. Thank you, Luis.
Mr Serrano thank you for existing.
Love that you broke down of concepts to micro level. Made the understanding of GAN's so simple and yet detailed. Appreciate it.
Thank you Luis for the simplified and very clear explanation. Finally, I feel that I can confidently understand the how GANs work. I also really liked the idea of the simple toy examples that you usually start to explain the complicated concepts.
Amazing summary of GANs with the simplest but concise explanations. Thank you!
What a great explanation! It's amazing how you teach complex concepts in such an easy way. I have learned a lot from your videos. Mil gracias!
You really have a special talent to generalize and explain complex concept. You go through every questions that we could think about during your explanations and all of them are answered with such pedagogy.
My fellow data scientists were all about GANs, so I went to learn something about it so I know where I stand in regards of synthetic data. And I'm glad I stumbled upon your video. What a great introduction to the topic! I feel I understand a lot more of what has been said and done about GANs now. Thank you!
The simplest but most effective explanation I've seen on GAN...Thank you :)
Its really great to understand a complex concept like GAN in a simple way
You provide by far some of the most descriptive explanations of Neural Network architecture, Machine Learning & statistics out there! Thank you!
By the way, I think you forgot to subtract the bias from the result of the second, noisy image at 6:32. It should be -1.5 instead of -0.5 :)
Your explanations are so simple that anyone can understand !!!
Thank so much
I am now watching this while waiting for the laundry. Just great! I also realized that I learned a lot from you about pytorch! Thank you sir! Keep up the great job!
No words would appreciate this rich explanation. I do like the visuals, mathematics and codes when they come together. Also, Your language was easy and smooth. You made the complex topic so easy to comprehend. Great thanks.
The most informative and intuitive explanation of GANs, for a beginner this video is priceless as all other resources aren't so patient with the critical details and steps which doesn't help with the learning process
Love your explanations and visuals! Thanks again for all you do here Luis, you sir are a gentleman and a scholar🎓🍻
Just want to leave a comment so that more people could learn from your amazing videos! Many thanks for the wonderful and fun creation!!!
One of the best explanations of the subject I have ever seen, congratulations, you are an excellent teacher!
Excellent video. Teaches the basics in a very clear manner. Thank you very much!
brilliance is the ability to take the complex and reduce it to simplicity. Brilliant work!
Muchas gracias, Luis. Primer video que veo sobre las GAN y ya entendí el concepto. ¡Impecable!
Absolutely stunning explanation!
Wow, I never understood the error functions until now! Thank you Luis!
Thank you so much for this video! I haven't found any good video explaining GANs as you did!
This is a wonderful video, very easy to understand. You have presented such a complex part of deep learning in such a way that it looks so easy! Thank you so much.
Very nice and clear explaination. Everytime I'd need a recap on GANs, I come to this video. Having no code but simple math makes it more meaningful -- comparing the other channel's which includes ML libraries, that places as obstacles on our way to understand!
By far, the best explanation of GANS ever! Well done, sir. Many, many thanks!!!!
Sr. Luis Serrano, os seus ensinamentos são demasiado preciosos. Por favor, continue fazendo versões em língua espanhola. Muito obrigado.
Amazing presentation with high quality slides!
I had to watch this video a few times, pause and rewind etc. but it did help me understand the intricacies of GANs. Thank you very much.
Simple and easy narration. Thank you sir
Great Job Man. I understood the basics of GANs and now i can work with my StackGan project
This is a really great video! You are a very good teacher, great video quality, you offer both intuition, as well as a an applied example - the code. Good Job!
Finally Gan math explained is the most elegant way..Thank you Sir
This is how the teachers explain, thanks a lot
the best in GAN tutorials
Thank you very much for this awesome explanation, Luis. Very, very well done!
really nice illustrations!! Understand the gan now
Awsome, you make neural networks easy and interesting.
Thank you 🙏🏻
Really helpful! Explains GANs very simply for beginners!
This is one of the best explanation i ever read/watched
ThankYou Sir, your content is the best, the visuals you put into videos make it so much easier to understand concepts. Keep it going Sir.
Loved the Slanting people demo... Thanks Luis.
Such a simple and great explanation. Thank you!
What an amazing video. I really impressed by the example you provide to explain such a complex concept.
This video is really helpful to understand about GAN. The way of teaching is really awesome.I liked it a lot.
Interesting example of GAN. Really enjoy your video. Keep a good works
Wow, good job! You gave me a very good sense of how it works and explained the loss function really well. I finally understand. Thank you!
I didn't expect this video until the end of the video. This is really helpful! Thank you
Very informative for learning GAN's! Congratulations!
I was struggling to understand this.... Your video made it so clear and easy to understand... Thank you soooooooo much...... ☺
Thanks for the slow transition and yeah i am not really good in maths and not yet much into more harder python. Its really useful than other videos out there.
THIS IS SOOOOOOOOOOO DAMN GOOD. thanks a lot man. totally understood gans without even a computer vision background
If you know the basics of CNN or ML and you are looking to learn basics of GAN this video is for you....very well explained thankyou
This is the best explanation on the internet. Thanks a lot!
I finally understand the lost key of GAN! Thank you a lot!
Thank you for the clear explanation. Just a couple of comments:
a) In 6:35, I think it should be -1.5 (not -0.5)
b) When creating the discriminator, if the bias is -1 then the threshold between good/bad images should be lower than 1. Otherwise some of the real faces would be labelled as false…
you are right, having this confusion
Thank you very much for this nice and very helpful explanation of GANs.
very nice explanation... I started learning GAN from zero, only have basic understanding about CNN. and from this video, I now understand how GAN works. Thank you
The best tutor! Excellent tutorial sir.
Amazing explanation....
Love from India.....
Such a blessing to have you
Wonderfully explained, thank you for making this video!
Uau! Amazing! Thanks for the simplest explanation I've ever seen 🙂
Simply amazing explanation👍🙌
So good & Easy to understand. Ty ! So generous w your knowledge
SIMPLY THE BEST EXPLANTION
Thanks a lot sir for such an easy explanation...
Bravo, Luis Serrano!
you are the best AI teacher i have ever seen !
The best video so far that I have come across. It is very annoying that so many videos that teach ML uses some API (e.g. Keras) to give examples. It teaches how to use the API but it does not teach you how it really works. I wish more used this awesome method to teach concepts in ML.
Why would anyone dislike this? Seriously, why? Thank you sir!
Senor Luis Serrano: Ud. ha hecho una excelente demostración pedagógica sobre un tema que otros han convertido en mistificación. Trabajo en la interpretación de Edipo Rey, de Sófocles, y estoy tratando de traducir mis conocimientos sobre la comunicación hecha por un texto literario clásico que "pinta" los rasgos de sus personajes mediante relaciones opuestas, principalmente, análogas a las de los slanted portraits de los "retratos" usados por Ud. Muchos de esos "retratos" se acercan a las imágenes que Ud. llamaría "noisy" hasta el extremo de ser desechables por su policía ... y por mí. Quiero decir que, no solo en esto, sino en otros muchos aspectos, encuentro un acercamiento entre la herramienta matemática por Ud. expuesta y la que yo quiero usar ... pero no soy matemático. A pesar de ello, gracias a mi búsqueda serendípica, he logrado encontrarme con su Serrano.Academy, y seguiré orientándome por sus lecciones, con agradecimiento.
Luis truly "KISS" (keep it sweetie simple) machine learning and re-ignites my love of scratching math!!! Whenever i find anything hard to crack i just search it in your channel...... Minor typos at Generator's Derivatives 00:19:00 where D weights are missing and the notations of G weights and D weights get mixed up, though everything is correct in your codes. Kind of cool to work on the simple math and detect those typos... Thanks again Luis for democratizing complex knowledge!! =)
Its really wonderful explanation, amazing video for beginners, thank you:)
simply amazing. Thank you so much for your efforts🙏
wow, this is such a great explanation!
You are such a good teacher
OMG this is sooooooo friendly and easy to understand!!!!!! Thank you so much!!!!
You're the best man. u deserve a million subscribers
Simply amazing!
Great video ! Thank you very much sharing your knowledge so pedagocically !
Outstanding explanation!!!!
you really make things easy. thanks a lot.
Thank you a lot. I am always impressed by your videos.
Pure Gold! Keep it up!
WOW! best tutorial on machine learning ever! Thank you
Thanks for sharing,Crystal clear explanation.
I remember ,Every one requested u for this and never imagined that request will be granted soon.
If u are reading this, kindly give us an opportunity to talk with you on TH-cam live session.
Thank you! Hoping to have another live session soon, will post an announcement when I know when!
Great explanation! Cheers to all slantland people!!
best video for GANs thanks
Thankyou Luis!!!!! It really inspires me!!!!!!
Wow, Amazing explanation. Learnt alot.
Congratulations for the video. Thanks for sharing.
Hi Luis! Great Videos! I'm very impressed and happy to see my old friend on TH-cam!
Thanks Hyosang!! I also checked out your videos, they’re great! Happy to see you over here after so long, hope all is going well in your side, my friend!
Thank you for this great explanation! It's amazing :-)
Best explanation of GAN in YTB