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A Generative Adversarial Network (GAN) trained on the MNIST dataset, capable of creating fake but realistic looking MNIST digit images that appear to be drawn from the original dataset.

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machine-learning deep-learning deep-neural-networks generative-adversarial-network gan mnist-image-dataset discriminator generator

mnist-digit-generation-gan's Introduction

Hi, I'm Sunil! 👋

🚀 About Me

I am a Data Scientist, a seasoned Business Analyst, and a Change Leader.
I have expertise in the capital markets domain, specializing in securities trading, post-trade processing, and security operations.
I am passionate, constantly experimenting and learning about everything "Data" and related disciplines of Data Analysis, Machine Learning, and Deep Learning
I hold a Bachelor of Engineering Degree (BE) in Computer Science, Post Graduate Diploma (PGD) in Data Science, and Master of Science (MS) degree in Data Science

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