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GAN、NLP：Generative Adversarial Networks(GANs)Tutorial in Python

作者：禅与计算机程序设计艺术

1.简介

Generative Adversarial Networks (GANs), also known as GANs for short, are a type of deep learning model used to generate new data instances or images that appear realistic and plausible. They were originally proposed by Ian Goodfellow et al. in the year 2014 and have become one of the most popular techniques today in computer vision, image processing, and natural language processing tasks such as text synthesis, image generation, and captioning. The basic idea behind GANs is simple: two neural networks compete with each other in a game-theoretic manner. One network generates fake samples that look like the original ones while the other tries to discern between true and generated data points. This competition leads to an improvement in generator’s ability to produce more convincing outputs.

In this tutorial series we will cover the following topics:

  • What are generative adversarial networks?
  • How

本文标签： GANNLPGenerative Adversarial Networks(GANs)Tutorial in Python

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