Výsledky vyhľadávania - (( (statei OR stat) python code analysis ) OR ( (stateeeeeene OR stateee) python code analysis ))*

GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries.

Autori: Fachada, Nuno Fernandes, Daniel Fernandes, Carlos M. a ďalší

Zdroj: Future Internet; Sep2025, Vol. 17 Issue 9, p412, 28p

Predmety: LANGUAGE models, EXPERIMENTAL design, PYTHON programming language, GENERATIVE pre-trained transformers, QUANTITATIVE research, BENCHMARK problems (Computer science), CODE generators

A statistical approach to automated analysis of the low‐contrast object detectability test for the large ACR MRI phantom.

Autori: Golestani, Ali M. Gee, Julia M.

Zdroj: Journal of Applied Clinical Medical Physics; Jul2025, Vol. 26 Issue 7, p1-9, 9p

Predmety: LINEAR statistical models, IMAGING phantoms, QUALITY control, PYTHON programming language, MAGNETIC resonance imaging

Python Programming: Numerical Analysis/Machine Learning Series.

Autori: Doskas, Constantinos

Zdroj: ISSA Journal; Oct2023, Vol. 21 Issue 10, p34-38, 5p

Predmety: PYTHON programming language, NUMERICAL analysis, MACHINE learning

Regularized Maximum Likelihood Estimation for the Random Coefficients Model in Python.

Autori: Dunker, Fabian Mendoza, Emil Reale, Marco

Zdroj: Mathematics (2227-7390); Dec2025, Vol. 13 Issue 23, p3764, 29p

Predmety: PYTHON programming language, MAXIMUM likelihood statistics, CONSUMPTION (Economics), MATHEMATICAL programming, MULTILEVEL models, SCIENTIFIC computing

The state of the late Quaternary megafauna extinction debate: a systematic review and analysis.

Autori: Stewart, Mathew Peters, Carli Ziegler, Michael J. a ďalší

Zdroj: Frontiers in Mammal Science. 2025, p1-27. 27p.

Automation of Software Code Analysis Using Machine Learning Methods.

Autori: Moshkin, V. S. Dyrnochkin, A. A. Yarushkina, N. G.

Zdroj: Pattern Recognition & Image Analysis; Sep2023, Vol. 33 Issue 3, p417-424, 8p

GE-IA-NAM: gene–environment interaction analysis via imaging-assisted neural additive model.

Autori: Li, Jingmao Xu, Yaqing Ma, Shuangge a ďalší

Zdroj: Bioinformatics; Sep2025, Vol. 41 Issue 9, p1-9, 9p

Predmety: CANCER research, GENOTYPE-environment interaction, DIAGNOSTIC imaging, DEEP learning, EMPIRICAL research, COMPUTER simulation

Strong correlation of gene counts and differentially expressed genes between a 3′ RNA-Seq and an RNA hybridization platform in transcriptome analyses from canine archival tissues.

Autori: Haake, Alexander F. H. Loriani Fard, Alina K. Jovanovic, Vladimir M. a ďalší

Zdroj: Frontiers in Veterinary Science. 2025, p1-13. 13p.

Time Series Analysis with Python Cookbook : Practical Recipes for the Complete Time Series Workflow, From Modern Data Engineering to Advanced Forecasting and Anomaly Detection

Autori: Tarek A. Atwan

Typ zdroja: eBook.

Predmet: Python (Computer program language), Machine learning

Kategórie: COMPUTERS / Data Science / Data Modeling & Design, COMPUTERS / Data Science / General, COMPUTERS / Data Science / Data Analytics

Genome-wide analyses reveal intricate genetic mechanisms underlying egg production efficiency in chickens.

Autori: Tan, Lizhi Cai, Xinyu Kong, Yuan a ďalší

Zdroj: Journal of Animal Science & Biotechnology. 8/11/2025, Vol. 16 Issue 1, p1-21. 21p.

Python Programming Log Analysis Series.

Autori: Doskas, Constantinos

Zdroj: ISSA Journal; Oct2021, Vol. 19 Issue 10, p20-23, 4p

Predmety: PYTHON programming language, SAWLOGS, RECORDS management, INFORMATION assurance, DATABASES, TEXT files

Portable Electronic Olfactometer for Non-Invasive Screening of Canine Ehrlichiosis: A Proof-of-Concept Study Using Machine Learning.

Autori: Durán Cotrina, Silvana Valentina Acevedo, Cristhian Manuel Durán Carrillo Gómez, Jeniffer Katerine

Zdroj: Veterinary Sciences. Jan2026, Vol. 13 Issue 1, p88. 20p.

Unsupervised Voting for Detecting the Algorithmic Solving Strategy in Competitive Programming Solutions.

Autori: Stoica, Alexandru Stefan Babiceanu, Daniel Mihaescu, Marian Cristian a ďalší

Zdroj: Mathematics (2227-7390); Nov2025, Vol. 13 Issue 22, p3589, 19p

Predmety: MACHINE learning, CLUSTERING algorithms, COMPUTER science, ALGORITHMS, SOURCE code

Compound-SNE: comparative alignment of t-SNEs for multiple single-cell omics data visualization.

Autori: Cess, Colin G Haghverdi, Laleh

Zdroj: Bioinformatics; Jul2024, Vol. 40 Issue 7, p1-5, 5p

Predmety: RESEARCH personnel, DATA visualization, GENE expression, DATA analysis, PYTHON programming language

ASAS-NANP symposium: mathematical modeling in animal nutrition—Making sense of big data and machine learning: how open-source code can advance training of animal scientists.

Autori: Brennan, Jameson R. Menendez, III, Hector M. Ehlert, Krista a ďalší

Zdroj: Journal of Animal Science. Jan2023, Vol. 101 Issue 1, p1-11. 11p. 4 Diagrams, 3 Graphs.

SparseCoder: Advancing source code analysis with sparse attention and learned token pruning.

Autori: Yang, Xueqi Jakubowski, Mariusz Kang, Li a ďalší

Zdroj: Empirical Software Engineering; Feb2025, Vol. 30 Issue 1, p1-30, 30p

Data-Driven Early Warning Approach for Antimicrobial Resistance Prediction–Anomaly Detection Based on High-Level Indicators.

Autori: Csorba, Szilveszter Vribék, Krisztián Farkas, Máté a ďalší

Zdroj: Veterinary Sciences. Oct2025, Vol. 12 Issue 10, p935. 17p.

Zinc as a Biomarker of Nutritional Status and Clinical Burden in Recessive Dystrophic Epidermolysis Bullosa: Implications for Preventive Monitoring.

Autori: Quintana-Castanedo, Lucía Maseda, Rocío Sánchez-Ramón, Silvia a ďalší

Zdroj: Nutrients. Jan2026, Vol. 18 Issue 2, p232. 19p.

An extensive study of the effects of different deep learning models on code vulnerability detection in Python code.

Autori: Wang, Rongcun Xu, Senlei Ji, Xingyu a ďalší

Zdroj: Automated Software Engineering; Jun2024, Vol. 31 Issue 1, p1-35, 35p

Programmed differently? Testing for gender differences in Python programming style and quality on GitHub.

Autori: Brooke, Siân

Zdroj: Journal of Computer-Mediated Communication; Jan2024, Vol. 29 Issue 1, p1-13, 13p

Predmety: PYTHON programming language, PYTHONS, RANDOM forest algorithms, GENDER