datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
hnm-fashion-recommendations-data
Dataset Rekomendasi Fashion H&M
Dataset ini berisi data transaksi, atribut pelanggan, dan metadata produk yang telah dianonimkan dari H&M Group. Kumpulan data komprehensif ini memungkinkan pemodelan perilaku pembelian pelanggan secara mendalam.
Wawasan yang dihasilkan dapat dimanfaatkan untuk berbagai tujuan bisnis yang strategis, mulai dari meningkatkan personalisasi pengalaman berbelanja, mengoptimalkan manajemen inventaris untuk efisiensi produksi, hingga mendukung inisiatif… See the full description on the dataset page: https://huggingface.co/datasets/einrafh/hnm-fashion-recommendations-data.Frappe_x1
Frappe_x1
Dataset description:
The Frappe dataset contains a context-aware app usage log, which comprises 96203 entries by 957 users for 4082 apps used in various contexts. It has 10 feature fields including user_id, item_id, daytime, weekday, isweekend, homework, cost, weather, country, city. The target value indicates whether the user has used the app under the context. Following the AFN work, we randomly split the data into 7:2:1 as the training set, validation set, and test set… See the full description on the dataset page: https://huggingface.co/datasets/reczoo/Frappe_x1.RecetasDeLaAbuela
Motivación inicial
Este corpus ha sido creado durante el Hackathon SomosNLP Marzo 2024: #Somos600M (https://somosnlp.org/hackathon).
Responde a una de las propuestas somosnlp sobre 'Recetas típicas por país/zona geográfica'.
Nombre del Proyecto
Este corpus o dataset se llama 'RecetasDeLaAbuel@' y es un homenaje a todas nuestr@s abuel@s que nos han enseñado a cocinar. Se trata de la mayor y más completa colección de recetas open-source en español de países… See the full description on the dataset page: https://huggingface.co/datasets/somosnlp/RecetasDeLaAbuela.aksahaha_crop-recommendation
crop recommendation
Crop Growth Recommendations: Optimal Conditions for Higher Yields
Dataset Info
Source: Kaggle
Original Size: 0.06 MB
Kaggle Downloads: 4,065
Files: 1
Files
Crop_recommendation.csv
Mirrored from Kaggle
Crop-recommendationCrop-Recommendation-Parameters
🌱 Crop Recommendation Dataset
A machine learning dataset for crop recommendation based on soil properties and environmental conditions. The dataset contains measurements of essential soil nutrients and climatic parameters, along with the crop label that is suitable for those conditions.
This dataset can be used for machine learning classification, agricultural analytics, decision-support systems, and smart farming applications.
📌 Dataset Overview
Property… See the full description on the dataset page: https://huggingface.co/datasets/Samarth-27/Crop-Recommendation-Parameters.recipes_data_food.comCriteo_x1
Criteo_x1
Dataset description:
The Criteo dataset is a widely-used benchmark dataset for CTR prediction, which contains about one week of click-through data for display advertising. It has 13 numerical feature fields and 26 categorical feature fields. Following the AFN work, we randomly split the data into 7:2:1* as the training set, validation set, and test set, respectively.
The dataset statistics are summarized as follows:
Dataset Split
Total
#Train
#Validation
#Test… See the full description on the dataset page: https://huggingface.co/datasets/reczoo/Criteo_x1.compas-recidivismPort of the compas-recidivism dataset from propublica (github here). See details there and use carefully, as there are serious known social impacts and biases present in this dataset.
Basic preprocessing done by the imodels team in this notebook.
The target is the binary outcome is_recid.
Sample usage
Load the data:
from datasets import load_dataset
dataset = load_dataset("imodels/compas-recidivism")
df = pd.DataFrame(dataset['train'])
X = df.drop(columns=['is_recid'])
y =… See the full description on the dataset page: https://huggingface.co/datasets/imodels/compas-recidivism.REC_SYSfood-recipeschile-seismological-records
Chile's Seismological Records
iPinYou_x1
iPinYou_x1
Dataset description:
The iPinYou Global Real-Time Bidding Algorithm Competition is organized by iPinYou from April 1st, 2013 to December 31st, 2013.The competition has been divided into three seasons. For each season, a training dataset is released to the competition participants, the testing dataset is reserved by iPinYou. The complete testing dataset is randomly divided into two parts: one part is the leaderboard testing dataset to score and rank the participating… See the full description on the dataset page: https://huggingface.co/datasets/reczoo/iPinYou_x1.TaobaoAd_x1
TaobaoAd_x1
Dataset description:
Taobao is a dataset provided by Alibaba, which contains 8 days of ad click-through data (26 million records) that are randomly sampled from 1140000 users. By default, the first 7 days (i.e., 20170506-20170512) of samples are used as training samples, and the last day's samples (i.e., 20170513) are used as test samples. Meanwhile, the dataset also covers the shopping behavior of all users in the recent 22 days, including totally seven hundred million… See the full description on the dataset page: https://huggingface.co/datasets/reczoo/TaobaoAd_x1.Criteo_x4
Criteo_x4
Dataset description:
The Criteo dataset is a widely-used benchmark dataset for CTR prediction, which contains about one week of click-through data for display advertising. It has 13 numerical feature fields and 26 categorical feature fields. Following the setting with the AutoInt work, we randomly split the data into 8:1:1 as the training set, validation set, and test set, respectively.
The dataset statistics are summarized as follows:
Dataset Split
Total
#Train… See the full description on the dataset page: https://huggingface.co/datasets/reczoo/Criteo_x4.recipes-with-nutritionLeverage our Recipes Dataset to explore one of the most comprehensive collections of structured recipe and nutrition data.
This dataset contains 39,447 recipes, enriched with detailed nutritional information, ingredient breakdowns, dietary classifications, and recipe metadata. Each record includes both raw recipe text (such as ingredient lines) and structured fields (nutritional values, cuisine type, diet/health labels, and more).
Designed as a rich, high-quality resource, this dataset… See the full description on the dataset page: https://huggingface.co/datasets/datahiveai/recipes-with-nutrition.Campus_Recruitment_CSV
Dataset Description
This data set consists of Placement data of students in a XYZ campus. Based on the student's performance data we are classifying his Placement Status.
The students report includes the following information:
CGPA - The grade of the student in his university
Internships - The no of internship done by the student before final placement
Projects - The no of projects done by the student
Workshops/Certifications - The no of workshops attended and the certifications… See the full description on the dataset page: https://huggingface.co/datasets/Krooz/Campus_Recruitment_CSV.Avazu_x1
Avazu_x1
Dataset description:
This dataset contains about 10 days of labeled click-through data on mobile advertisements. It has 22 feature fields including user features and advertisement attributes. The preprocessed data are randomly split into 7:1:2* as the training set, validation set, and test set, respectively.
The dataset statistics are summarized as follows:
Dataset
Total
#Train
#Validation
#Test
Avazu_x1
40,428,967
28,300,276
4,042,897
8,085,794
Source:… See the full description on the dataset page: https://huggingface.co/datasets/reczoo/Avazu_x1.recipeCriteo_x2
Criteo_x2
Dataset description:
This dataset employs the Criteo 1TB Click Logs for display advertising, which contains one month of click-through data with billions of data samples. Following the same setting with the AutoGroup work, we select "data 6-12" as the training set while using "day-13" for testing. To reduce label imbalance, we perform negative sub-sampling to keep the positive ratio roughly at 50%. It has 13 numerical feature fields and 26 categorical feature fields. In… See the full description on the dataset page: https://huggingface.co/datasets/reczoo/Criteo_x2.fakerecogna2-abstrativa
FakeRecogna 2.0 - Abstractive
FakeRecogna 2.0 presents the extension for the FakeRecogna dataset in the context of fake news detection. FakeRecogna includes real and fake news texts collected from online media and ten fact-checking sources in Brazil. An important aspect is the lack of relation between the real and fake news samples, i.e., they are not mutually related to each other to avoid intrinsic bias in the data.
The Dataset
The fake news collection was performed on… See the full description on the dataset page: https://huggingface.co/datasets/recogna-nlp/fakerecogna2-abstrativa.RecurrReason
RecurrReason: Recurrent Reasoning on Symbolic Puzzles
A difficulty-controlled benchmark for evaluating multi-step reasoning in language models
📋 Table of Contents
Overview
Dataset Structure
Puzzles
Quick Start
Citation
License
🎯 Overview
RecurrReason is a benchmark of four recurrent logic puzzles with optimal trajectories and controlled difficulty scaling (N=1 to 10). It tests whether language models can:
Find optimal (minimal-length)… See the full description on the dataset page: https://huggingface.co/datasets/gmannem/RecurrReason.pubmedqa-recursive-llm-degradation-qwen2.5-0.5b
PubMedQA Recursive LLM Degradation — Qwen2.5-3B
This repository contains synthetic biomedical question-answering data
and model predictions generated as part of a study of recursive
fine-tuning and model degradation.
Base Model
Qwen/Qwen2.5-3B
Source Dataset
The experiments use the PubMedQA dataset:
qiaoxin/PubMedQA
This repository contains generated/derived research artifacts and does
not redistribute the original PubMedQA dataset in its entirety.… See the full description on the dataset page: https://huggingface.co/datasets/chrislimbe/pubmedqa-recursive-llm-degradation-qwen2.5-0.5b.fakerecogna2-extrativa
FakeRecogna 2.0 Extractive
FakeRecogna 2.0 presents the extension for the FakeRecogna dataset in the context of fake news detection. FakeRecogna includes real and fake news texts collected from online media and ten fact-checking sources in Brazil. An important aspect is the lack of relation between the real and fake news samples, i.e., they are not mutually related to each other to avoid intrinsic bias in the data.
The Dataset
The fake news collection was performed on… See the full description on the dataset page: https://huggingface.co/datasets/recogna-nlp/fakerecogna2-extrativa.pubmedqa-recursive-llm-degradation-qwen2.5-3b
PubMedQA Recursive LLM Degradation — Qwen2.5-3B
This repository contains synthetic biomedical question-answering data
and model predictions generated as part of a study of recursive
fine-tuning and model degradation.
Base Model
Qwen/Qwen2.5-3B
Source Dataset
The experiments use the PubMedQA dataset:
qiaoxin/PubMedQA
This repository contains generated/derived research artifacts and does
not redistribute the original PubMedQA dataset in its entirety.… See the full description on the dataset page: https://huggingface.co/datasets/chrislimbe/pubmedqa-recursive-llm-degradation-qwen2.5-3b.twin-cities-public-records
Twin Cities public records, joined
25 datasets · 1,575,384 rows · free, CC BY 4.0 · mirrored from brickandmortar.dev
A city emits records constantly — parcels, recorded sales, assessments, permits, licences, inspections, 911 calls, cleanup sites, flood zones, federal loans, wages, census measures — and almost nobody joins them. These are the joined slices, published as files rather than as an API you have to ask for a key to. The join is the work; the data is free.
This is a… See the full description on the dataset page: https://huggingface.co/datasets/brickandmortar/twin-cities-public-records.recalldb-product-recalls-sample
RecallDB — U.S. Product Recall Database (Sample)
Full dataset: recalldb.dataengineered.io · $49 one-time snapshot → Buy on Stripe · the same sample on Kaggle
127,783 official recalls · 292,790 recalled products · CPSC · FDA · FSIS · NHTSA · USCG · 100% source-linked
RecallDB is a normalized, provenance-tracked dataset of official U.S. federal product recalls. It joins five official source families into one relational model: CPSC consumer products, NHTSA vehicles, FDA/openFDA… See the full description on the dataset page: https://huggingface.co/datasets/Ichlibitiche/recalldb-product-recalls-sample.bio-bite-recovery-nutrition
Bio-Bite — Recovery Nutrition Dataset
A synthetic dataset of 10,000 recovery profiles paired with matching recovery recipes. Each row links a physiological state (strain, sleep, HRV) to a rule-grounded nutritional target and a generated recipe intended to address it.
Built for the Bio-Bite project: an app that reads the recovery data a smartwatch already collects — strain, sleep, HRV — and turns it into a personalized recovery meal and a next-day plan.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/benjac8/bio-bite-recovery-nutrition.Avazu_x4
Avazu_x4
Dataset description:
This dataset contains about 10 days of labeled click-through data on mobile advertisements. It has 22 feature fields including user features and advertisement attributes. Following the same setting with the AutoInt work, we split the data randomly into 8:1:1 as the training set, validation set, and test set, respectively.
The dataset statistics are summarized as follows:
Dataset
Total
#Train
#Validation
#Test
Avazu_x4
40,428,967
32,343,172… See the full description on the dataset page: https://huggingface.co/datasets/reczoo/Avazu_x4.PHI-CTRL-F16-Fault-Recovery-Telemetry
PHI-CTRL F-16 Actuator Fault Recovery Dataset
High-Fidelity JSBSim 6-DOF Telemetry for Physics-Hybrid Self-Healing Flight Control
Official verification artifacts of the PHI-CTRL (Physics-Hybrid Integrity Control) architecture — a digital-twin-driven, self-healing flight control framework that actively compensates actuator degradation in real time.
Author: Mohammed Bello Sani (SM-Bello)
Affiliation: Air Force Institute of Technology (AFIT), Kaduna · Penelope Inc. / PHI Lab… See the full description on the dataset page: https://huggingface.co/datasets/SM-Bello/PHI-CTRL-F16-Fault-Recovery-Telemetry.