spring-tips/data-oriented-programming-in-java-21
Hi, Spring fans! In this installment we look at one of my favorite paradigms in Java 21 and later: Data Oriented Programming (⭐ 11)
GalliformeSpectra: A Hen Breed Dataset
This article presents a comprehensive dataset featuring ten distinct hen breeds, sourced from various regions, capturing the unique characteristics and traits of each breed. The dataset encompasses Bielefeld, Blackorpington, Brahma, Buckeye, Fayoumi,...
Information Flows for Athletes' Health and Performance Data
Increasing numbers of athletes and sports teams use data collection technologies to improve athletic development and athlete health with the goal of improving competitive performance. Personal data privacy is managed but it is not always a priority f...
garmin-data/garmdown
Download Garmin Connect Data (⭐ 17)
Autonomous Deep Learning: Incremental Learning of Denoising Autoencoder for Evol…
The generative learning phase of Autoencoder (AE) and its successor Denosing Autoencoder (DAE) enhances the flexibility of data stream method in exploiting unlabelled samples. Nonetheless, the feasibility of DAE for data stream analytic deserves in-d...
Data monitoring committee - Wikipedia
A data monitoring committee (DMC) – sometimes called a data and safety monitoring board (DSMB) – is an independent group of experts who monitor patient
Reasoning about Independence in Probabilistic Models of Relational Data
We extend the theory of d-separation to cases in which data instances are not independent and identically distributed. We show that applying the rules of d-separation directly to the structure of probabilistic models of relational data inaccurately i...
MEDAL: An AI-driven Data Fabric Concept for Elastic Cloud-to-Edge Intelligence
Current Cloud solutions for Edge Computing are inefficient for data-centric applications, as they focus on the IaaS/PaaS level and they miss the data modeling and operations perspective. Consequently, Edge Computing opportunities are lost due to cumb...
PyWiFeS: A Rapid Data Reduction Pipeline for the Wide Field Spectrograph (WiFeS)
We present PyWiFeS, a new Python-based data reduction pipeline for the Wide Field Spectrograph (WiFeS). PyWiFeS consists of a series of core data processing routines built on standard scientific Python packages commonly used in astronomical applicati...
When would online platforms pay data dividends
Online platforms, including social media and search platforms, have routinely used their users' data for targeted ads, to improve their services, and to sell to third-party buyers. But an increasing awareness of the importance of users' data privacy...
COVID-19 Pneumonia Severity Prediction using Hybrid Convolution-Attention Neural…
This study proposed a novel framework for COVID-19 severity prediction, which is a combination of data-centric and model-centric approaches. First, we propose a data-centric pre-training for extremely scare data scenarios of the investigating dataset...
VideoMind: An Omni-Modal Video Dataset with Intent Grounding for Deep-Cognitive…
This paper introduces VideoMind, a video-centric omni-modal dataset designed for deep video content cognition and enhanced multi-modal feature representation. The dataset comprises 103K video samples (3K reserved for testing), each paired with audio...
YouGov data and research
Access free public data, surveys, articles, trackers and rankings. Explore YouGov’s comprehensive research that combines real-world data with expert analysis.
Technion-Kishony-lab/data-to-paper
data-to-paper: Backward-traceable AI-driven scientific research (⭐ 761)
MHassaanButt/Pulling-Data-from-ESPN-of-NCAAF
In this project, I pull the data of College Football matches play by play. (⭐ 4)
A Conjoint Application of Data Mining Techniques for Analysis of Global Terroris…
Terrorism has become one of the most tedious problems to deal with and a prominent threat to mankind. To enhance counter-terrorism, several research works are developing efficient and precise systems, data mining is not an exception. Immense data is...
Semi-Supervised Learning under General Causal Models
Semi-supervised learning (SSL) aims to train a machine learning model using both labelled and unlabelled data. While the unlabelled data have been used in various ways to improve the prediction accuracy, the reason why unlabelled data could help is n...
gurgeh/data-preppy
Python scripts for doing data preparation on CSV files, mostly without loading them into memory. (⭐ 5)
Investigating myocardial infarction and its effects in patients with urgent medi…
In medical science, it is very important to gather multiple data on different diseases and one of the most important objectives of the data is to investigate the diseases. Myocardial infarction is a serious risk factor in mortality and in previous st...
ALP: Data Augmentation using Lexicalized PCFGs for Few-Shot Text Classification
Data augmentation has been an important ingredient for boosting performances of learned models. Prior data augmentation methods for few-shot text classification have led to great performance boosts. However, they have not been designed to capture the...