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open Graph Image
photo
open Graph Image
photo
is In Organization
No
is In Organization
Yes
description
In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.
description
Spring Boot
homepage
homepage
https://spring.io/projects/spring-boot
url
https://githubhelp/hungchun-lin/stock-price-prediction-using-gan
url
https://githubhelp/spring-projects/spring-boot
disk Usage
107423
dis kUsage
172819
stargazer Count
200
stargazer Count
73164
forkCount
95
forkCount
40137
watcher Count
200
watcher Count
73164
created At
2020-09-21
created At
2012-10-19
license Info
MIT License
license Info
Apache License 2.0
issues
15
issues
50
languages
2
languages
13
repository Topics
5
repository Topics
4
owner
hungchun-lin
owner
spring-projects
owner Avatar
photo
owner Avatar
photo
other
other

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