Published in


A Brief Introduction To GANs

With explanations of the math and code

GANs, or Generative Adversarial Networks, are a type of neural network architecture that allow neural networks to generate data. In the past few years, they’ve become one of the hottest subfields in deep learning, going from generating fuzzy images of digits to photorealistic images of faces.




Making Machine Learning more accessible. One line of code at a time.

Recommended from Medium

One Bump or Two: An Investigation Into Collision Detection in Agent-Based Modeling

Minimum steps for implementing a Machine Learning algorithm

Top Hacks To Learn Machine Learning.

Machine Learning Project 1: Predict Salary using Simple Linear Regression

As predicted delayed outputs settle in NarX

Combination of Abstractive & Extractive methods for Text Summarization (Tutorial 7)

How to run Keras model on Movidius neural compute stick

Understanding Backpropagation Algorithm

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Sarvasv Kulpati

Sarvasv Kulpati

Writing about technology, philosophy, and everything in between.

More from Medium

Corrosivity index and streamflow to evaluate trends in potentially corrosive source waters in the…

Towards understanding ML predictions — Introduction

A common mistake to avoid in Machine Learning projects

Things to remember before using Machine Learning Algorithms