# hungchun-lin/Stock-price-prediction-using-GAN

<https://repo.masters-masters.com/repos/hungchun-lin/Stock-price-prediction-using-GAN>

[Accueil](https://repo.masters-masters.com/) › [hungchun-lin](https://repo.masters-masters.com/owners/hungchun-lin) › [Stock-price-prediction-using-GAN](https://repo.masters-masters.com/repos/hungchun-lin/Stock-price-prediction-using-GAN)

hungchun-lin/Stock-price-prediction-using-GAN, dépôt open source à 270 étoiles sur GitHub. Carte Alpha de RepoMasters. In this project, we will compare two…

| Champ | Valeur |
| --- | --- |
| Propriétaire | [hungchun-lin](https://repo.masters-masters.com/owners/hungchun-lin) |
| Étoiles | 270 |
| Forks | 106 |
| Langage | [Jupyter Notebook](https://repo.masters-masters.com/languages/jupyter-notebook) |
| Licence | MIT |
| Création | 2020 |
| Sujets | stock-prediction, gan, lstm, gru, python |
| Rang | [Alpha (250 à 699 ★)](https://repo.masters-masters.com/ranks/b_movie) |
| Voir sur GitHub | [hungchun-lin/Stock-price-prediction-using-GAN](https://github.com/hungchun-lin/Stock-price-prediction-using-GAN) |

## Fiche du dépôt

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 utili…

Rang des dépôts qui ont 250 à 699 ★ sur GitHub. Probabilité publiée par carte tirée : 20 %. Rareté : Peu commune.

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Données : GitHub · Illustration dessinée par RepoMasters à partir de l’identifiant du dépôt et de la couleur de son langage.