AI Scope
@scopeofai
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AI Scope
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first introduced in 2014
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GAN uses two sub-models
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Generator and Discriminator
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Generator is responsible to generate from the given data and discriminator has to say if it is fake or not
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the practice and learn continues till the discriminator is unable to tell if generated data is fake or real
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https://youtu.be/8L11aMN5KY8?si=mzqhsXsIA4pc1hnO
YouTube
A Friendly Introduction to Generative Adversarial Networks (GANs)
Code: https://www.github.com/luisguiserrano/gans
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: htt…
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AI Scope
a really fascinating video about GAN with an interesting example of building a GAN from scratch
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the code of the example in this video: https://github.com/luisguiserrano/gans/blob/master/GANs_in_Slanted_Land.ipynb?short_path=28407f0
GitHub
gans/GANs_in_Slanted_Land.ipynb at master · luisguiserrano/gans
GANs in slanted land. Contribute to luisguiserrano/gans development by creating an account on GitHub.
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holy shit the math
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and this is just a beginning and the simplest form of math
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https://machinelearningmastery.com/what-are-generative-adversarial-networks-gans/
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a comprehensive guide to GAN
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real simple blog
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https://www.youtube.com/watch?v=eyxmSmjmNS0&t=1170s
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a really advanced approach to GAN
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https://www.youtube.com/watch?v=eyxmSmjmNS0&t=1170s
watch this to feel smart
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Forwarded from Machine Learning
Mathematics_for_Machine_Learning .pdf
1.4 MB
MATHEMATICS FOR MACHINE LEARNING

A Comprehensive Guide to Building Mathematical Foundations for AI and Data Science

@machine_learning_and_DL
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I'm terrified and excited at the same time
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This is gonna be an enjoyable journey I gotta tell you that
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