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Adding little noise can lead for DL models to miss-classify. The funny thing is that the model’s confidence in wrongly classifying the item is more than when it calculates the correct predictions. All this happens due to a small noise that we introduce into the data. This can be only improved by training on more data and the inspiration around t…

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Face Generation GANs

This project is a part of CSCI-P 556 APPLIED MACHINE LEARNING course during my Master's Data Science at Indiana University Bloomington

Syllabus : Project Details

Milestone 1 : Project Proposal

Milestone 2 : Progress Report

Submsission Code : GANs Face Generators

Final Presentation : Slides

Step by Step Output of Generating Realistic Faces from random noise

Generated Image + Neural Style Transfer

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Adding little noise can lead for DL models to miss-classify. The funny thing is that the model’s confidence in wrongly classifying the item is more than when it calculates the correct predictions. All this happens due to a small noise that we introduce into the data. This can be only improved by training on more data and the inspiration around t…

deep-neural-networks deep-learning pytorch generative-adversarial-network

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