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

Performance of machine learning algorithms. by Wenxue Liu (6877754)

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. …”

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

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." …”

Flowchart of DQN algorithm. by Jiandong Qiu (20389944)

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).…”

<b>Discrimination of gold deposit types based on big data analysis and machine learning techniques</b> by Lihao Feng (20837036)

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

The genome coding scheme. by Wenbing Shi (5806160)

Subjects:

Example measurement and analysis units for landscape elements. by Jaewon Han (8660295)

Subjects:

Risk element category diagram. by Yao Hu (3479972)

“…This article used these data to establish an LSTM model, which trained LSTM to identify potential risks and provide early warning by learning patterns and trends in historical data. …”

Source Code and Dataset by Swathi Ganesan (14394924)

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. by Abdullah Asım Yılmaz (20715311)

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

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. …”