# ajayarunachalam/Deep\_XF

<https://repo.masters-masters.com/repos/ajayarunachalam/Deep_XF>

[Accueil](https://repo.masters-masters.com/) › [ajayarunachalam](https://repo.masters-masters.com/owners/ajayarunachalam) › [Deep\_XF](https://repo.masters-masters.com/repos/ajayarunachalam/Deep_XF)

ajayarunachalam/Deep\_XF, dépôt open source à 119 étoiles sur GitHub. Carte Prototype de RepoMasters. Package towards building Explainable Forecasting and…

| Champ | Valeur |
| --- | --- |
| Propriétaire | [ajayarunachalam](https://repo.masters-masters.com/owners/ajayarunachalam) |
| Étoiles | 119 |
| Forks | 24 |
| Langage | [Jupyter Notebook](https://repo.masters-masters.com/languages/jupyter-notebook) |
| Licence | Aucune |
| Création | 2021 |
| Sujets | python, forecasting, nowcasting-models, forecasting-models, explainable-ml, deep-neural-networks, deep-learning, time-series, time-series-analysis, auto-ml |
| Rang | [Prototype (100 à 249 ★)](https://repo.masters-masters.com/ranks/rush) |
| Voir sur GitHub | [ajayarunachalam/Deep\_XF](https://github.com/ajayarunachalam/Deep_XF) |

## Fiche du dépôt

Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeser…

Rang des dépôts qui ont 100 à 249 ★ sur GitHub. Probabilité publiée par carte tirée : 70 %. Rareté : 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.