Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code by Goutami Sooda (20714729)

Data and code resources. by Sam Hall-McMaster (10343795)

“…Decoding from functional magnetic resonance imaging data revealed that solutions from the SF&GPI algorithm were activated on test tasks in visual and prefrontal cortex. …”

Code and data for the paper "Investigating machine learning algorithms to classify label-free images of pancreatic neuroendocrine neoplasms" by Noelle Madyson Daigle (22120114)

“…<p dir="ltr">Code and data for analysis detailed in the paper "Investigating machine learning algorithms to classify label-free images of pancreatic neuroendocrine neoplasms." …”

Research data for paper: Efficient Event-based Delay Learning in Spiking Neural Networks by Balázs Mészáros (16890225)

“…<p dir="ltr">The data in this repository accompanies the paper 'Efficient Event-based Delay Learning in Spiking Neural Networks'</p><p dir="ltr">The data relates to 4 benchmarks:</p><ol><li>Spiking Heidelberg Digits (SHD).…”

The genome coding scheme. by Wenbing Shi (5806160)

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Source Code and Dataset by Swathi Ganesan (14394924)

code_4 by Olga Ovtsarenko (20432033)

Data and code availability: Machine Learning on systematically curated data reveals key determinants of magnetic hyperthermia performance by Edgar Vega (21981590)

“…Twelve machine learning models were evaluated and refined using Bayesian hyperparameter optimization. …”

The accuracy of all employed learning algorithms. by Quan Shao (20148209)

Code used for data analysis in this study. by Nourin Sultana (22339463)

“…This study applies and evaluates machine learning (ML) algorithms to predict LBW and identify its key risk factors in Bangladesh. …”

Machine learning algorithms hyperparameter values. by Mahbub E. Sobhani (22278967)

Types of machine learning algorithms. by Md. Merajul Islam (12646837)

“…Thus, the objectives of this study are to develop an appropriate model for predicting the risk of undernutrition and identify its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.</p><p>Materials and methods</p><p>This study used the latest nationally representative cross-sectional Bangladesh demographic health survey (BDHS), 2017–18 data. …”

Computational Domain: The computational domain was discretized using conformal tetrahedral elements, resulting in a total of 926K elements. by Martina Bukač (20161460)

Description of the dataset used for the machine learning algorithm. by Tri Ngo Quang (20390189)

Performance of different machine learning algorithms. by Apichat Suratanee (634281)

Parameters of the machine learning algorithms used in the study. by Xiaoyan Yang (259084)

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Data_Sheet_1_Sex differences in brain MRI using deep learning toward fairer healthcare outcomes.PDF by Mahsa Dibaji (20177271)

“…<p>This study leverages deep learning to analyze sex differences in brain MRI data, aiming to further advance fairness in medical imaging. …”

The performance matrix of different machine learning algorithms. by Ahmad M. Al-Omari (20460931)

Machine learning prediction algorithm flow chart. by Ahmad M. Al-Omari (20460931)

S1 Data - by Wenbing Shi (5806160)

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