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)

Subjects:

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

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

Visualization process of AOSD algorithm. by Lu Liu (171341)

K-SVD dictionary learning process. by Li Jiaqing (21212614)

Subjects:

Hardware_code. by Mehdi Nadiri Andabili (22097275)

“…As a result of its low power consumption, minimal error rates, and high-frequency capabilities, the proposed hardware demonstrates effectiveness and utility across a range of applications, including the simulation of learning processes in the nervous system that are based on nonlinear and chaotic behaviors.…”

Software_code. by Mehdi Nadiri Andabili (22097275)

“…As a result of its low power consumption, minimal error rates, and high-frequency capabilities, the proposed hardware demonstrates effectiveness and utility across a range of applications, including the simulation of learning processes in the nervous system that are based on nonlinear and chaotic behaviors.…”

Training process of triplet loss in federated learning. by Chunjuan Li (7890182)

Schematic diagram of the transfer learning process. by Guoqing Zhang (151441)

Effects of processing rate and algorithms performance on estimates of biodiversity. by Valentine Fleuré (12822137)

Subjects:

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

“…Our code and saliency maps are available at https://github.com/mahsadibaji/sex-differences-brain-dl.…”

The GTO algorithm process. by Yulin Li (36434)

Fractional Cross-Validation for Optimizing Hyperparameters of Supervised Learning Algorithms by Suraj Yerramilli (21510476)

“…In this work, we propose a highly-efficient Bayesian optimization algorithm for optimizing the hyperparameters of supervised learning algorithms with K-fold CV error as the evaluation criterion. …”

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

Computational Micromechanics and Machine Learning-Informed Design of Composite Carbon Fiber-Based Structural Battery for Multifunctional Performance Prediction by Mohamad A. Raja (19640297)

Subjects: “…bayesian optimization algorithm…”

Reinforcement learning process based on overflow prediction. by Yulin Tian (1457986)

Subjects:

Processed results from ECG data with the P-T algorithm. by Daehyun Kwon (11985629)

Results obtained from the supervised machine learning regression-based algorithms in the present work. by Akshansh Mishra (21001499)

Subjects:

The Search process of the genetic algorithm. by Wenguang Li (6528113)

“…The results show: (1) Random oversampling, ADASYN, SMOTE, and SMOTEENN were used for data balance processing, among which SMOTEENN showed better efficiency and effect in dealing with data imbalance. (2) The GA-XGBoost model optimized the hyperparameters of the XGBoost model through a genetic algorithm to improve the model’s predictive accuracy. …”