ajayarunachalam / Deep_XF

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 timeseries signals.

Date Created 2021-10-26 (3 years ago)

Commits 22 (last one 2 years ago)

Stargazers 113 (0 this week)

Watchers 5 (0 this week)

Forks 23

License unknown

Ranking

RepositoryStats indexes 595,856 repositories, of these ajayarunachalam/Deep_XF is ranked #271,033 (55th percentile) for total stargazers, and #335,688 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #6,563/17,543.

ajayarunachalam/Deep_XF is also tagged with popular topics, for these it's ranked: python (#12,047/22324), deep-learning (#4,780/8512), machine-learning (#4,506/8063), time-series (#376/672), deep-neural-networks (#383/634), forecasting (#106/190), time-series-analysis (#77/151)

Other Information

ajayarunachalam/Deep_XF has Github issues enabled, there is 1 open issue and 1 closed issue.

All Topics

python auto-ml sensors ecg-signal timeseries forecasting time-series multivariate deep-learning explainable-ml auto-timeseries interpretable-ai machine-learning nowcasting-models forecasting-models deep-neural-networks time-series-analysis siamese-neural-network

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4 commits on the default branch (main) since jan '22

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The primary language is Jupyter Notebook but there's also others...

updated: 2024-12-21 @ 11:04am, id: 421340252 / R_kgDOGR0kXA