Code Monkey home page Code Monkey logo

gan-using-mnist_data's Introduction

GAN-using-Mnist_data

This is a practice to make Generative Adversial Network(GAN) by using MNist data in google colab.

Grayscale버전은 Mnist_gan_2으로 실험해봤습니다. gan_2에서는 목적 함수를 MSE 대신 cross entopy를 사용했습니다. 따라서 실험중 그레디언트(Loss)를 보면, 오류가 더 큰 쪽에 더 큰 벌점을 부과하는 경향이 보입니다.

실험 내용은 ppt에 첨부했습니다. 감사합니다!

gan-using-mnist_data's People

Contributors

leechunghyun avatar

Watchers

avatar avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.