What are GAN’s actually- from underlying math to python code
Build Basic Generative Adversarial Networks (GANs)
What you’ll learn
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GAN’s Topic Overview and Prerequisites
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Theoretical Concept behind GAN’s
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KL & JS Divergence
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Underlying math behind GAN’s : Min – Max Game
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DCGAN & Hands on Python
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Conditional GAN & Hands on Python
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ACGAN & Hands on Python
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Challenges in training the GAN’s
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Evaluation metrics & Tips for making GAN’S in real life
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Practical Application – Synthetic class specific image generation using GANs
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Some other cool applications of GAN’s
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Semi-supervised learning with Generative Adversarial Networks
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Hands on Semi-supervised learning with Generative Adversarial Network
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Summary & additional resources
Requirements
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A thorough understanding of computer vision & Neural Networks concepts
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Good command on Python for data science
Who this course is for:
- Beginner Python developers curious for understanding GAN’s, their underlying math, and getting your hands dirty with python.
- Beginner Python developers curious for some real life applications of GAN’s
