datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Multimodal-Dataset-Image_Text_Table_TimeSeries-for-Financial-Time-Series-ForecastingThe sp500stock_data_description.csv file provides detailed information on the existence of four modalities (text, image, time series, and table) for 4,213 S&P 500 stocks.
The hs300stock_data_description.csv file provides detailed information on the existence of four modalities (text, image, time series, and table) for 858 HS 300 stocks.
If you find our research helpful, please cite our paper:
@article{xu2025finmultitime,
title={FinMultiTime: A Four-Modal Bilingual Dataset for… See the full description on the dataset page: https://huggingface.co/datasets/Wenyan0110/Multimodal-Dataset-Image_Text_Table_TimeSeries-for-Financial-Time-Series-Forecasting.TreeSatAI-Time-Series
TreeSatAI-Time-Series
This dataset was introduced in the ECCV24 paper OmniSat.
Ahlswede et al. (https://essd.copernicus.org/articles/15/681/2023/) introduced the TreeSatAI Benchmark Archive, a new dataset for tree species classification in Central Europe based on multi-sensor data from aerial,
Sentinel-1 and Sentinel-2. The dataset contains labels of 20 European tree species (i.e., 15 tree genera) derived from forest administration data of the federal state of Lower Saxony… See the full description on the dataset page: https://huggingface.co/datasets/IGNF/TreeSatAI-Time-Series.faang-engineered-time-series-features-2013-2025
FAANG Stocks Historical Raw and Engineered Time-Series Dataset (2013-2025)
Since this is a comprehensive ReadMe file with multiple sections and crosslinks to other documents and images, I wanted to start by providing a ToC with hyperlinks to simplify navigation for the readers. (special thanks to @csavur for this very helpful suggestion!)
DOCUMENT NAVIGATION GUIDE (ToC)
1 - Summary2 - Usage & Reproducability3 - Practical Uses of this Dataset
3.1 - A real-world ML… See the full description on the dataset page: https://huggingface.co/datasets/ML-Owl/faang-engineered-time-series-features-2013-2025.Telecommunication_SMS_time_series
SMS Time series data for traffic and fraud forecasting. TeleWhale vendor collected data
This dataset contains various time series from vendors.
Shashkov A.A.
Vendor A: 01.03.23-14.08.23
TS_*_all - Count of all SMS
Vendor A: January
TS_*_fraud - Count of fraud
TS_*_all - Count of all SMS
TS_*_hlrDelay - Mean values of hlr delay
Vendor B: January 1-8
1-8_TS_*_fraud - Count of fraud
1-8_TS_*_all - Count of all SMS
1-8_TS_*_hlrDelay -… See the full description on the dataset page: https://huggingface.co/datasets/Shashkovich/Telecommunication_SMS_time_series.Multimodal-Dataset-Image_Text_Table_TimeSeries-for-Financial-Time-Series-ForecastingThe sp500stock_data_description.csv file provides detailed information on the existence of four modalities (text, image, time series, and table) for 4,213 S&P 500 stocks.
The hs300stock_data_description.csv file provides detailed information on the existence of four modalities (text, image, time series, and table) for 858 HS 300 stocks.
If you find our research helpful, please cite our paper:
@article{xu2025finmultitime,
title={FinMultiTime: A Four-Modal Bilingual Dataset for… See the full description on the dataset page: https://huggingface.co/datasets/Y123-wed/Multimodal-Dataset-Image_Text_Table_TimeSeries-for-Financial-Time-Series-Forecasting.AgroGate_SAR2NDVI_With_TIMESERIES
Dataset Card — AgroGate_SAR2NDVI_With_TIMESERIES
Dataset Summary
AgroGate_SAR2NDVI_With_TIMESERIES is a geospatial dataset containing paired SAR and NDVI satellite images of paddy fields collected across multiple growth stages within a single cultivation season.
Each SAR–NDVI pair is captured as close in time as possible (±7 days) to ensure accurate spectral correspondence, and several such pairs are included per paddy lifecycle (typically 3–4 months).
The dataset… See the full description on the dataset page: https://huggingface.co/datasets/SanuthK/AgroGate_SAR2NDVI_With_TIMESERIES.multimodal-time-series-forecasting