Suchergebnisse - (( ((stated OR stateed) OR statement) python code analysis ) OR ( state python code analysis ))~

Modelling a Lab-Scale Continuous Flow Aerobic Granular Sludge Reactor: Optimisation Pathways for Scale-Up.

Autoren: Siney, Melissa Salehi, Reza Hassan, Mohamed G. et al.

Quelle: Water (20734441); Jul2025, Vol. 17 Issue 14, p2131, 37p

Schlagwörter: CONTINUOUS flow reactors, MATHEMATICAL models, COMPUTATIONAL fluid dynamics, WASTEWATER treatment, SENSITIVITY analysis, CHEMICAL oxygen demand, CHEMICAL reactors

Luminescence Signal Analysis Using Python

Autoren: Vasilis Pagonis

Resource Type: eBook.

Schlagworte: Radiation dosimetry, Mathematical physics, Python (Computer program language), Quantum physics, Optical spectroscopy

Categories: SCIENCE / Life Sciences / Biophysics, COMPUTERS / Languages / Python, SCIENCE / Physics / Mathematical & Computational, SCIENCE / Physics / Quantum Theory, SCIENCE / Spectroscopy & Spectrum Analysis, TECHNOLOGY & ENGINEERING / Materials Science / General

Utilizing Deep Learning and Object-Based Image Analysis to Search for Low-Head Dams in Indiana, USA.

Autoren: Crookston, Brian M. Arnold, Caitlin R.

Quelle: Water (20734441); Mar2025, Vol. 17 Issue 6, p876, 24p

Schlagwörter: IMAGE analysis, WATER supply, DAMS, MODEL validation, LEARNING ability

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

Autoren: Tarek A. Atwan

Resource Type: eBook.

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

Applied Time Series Analysis and Forecasting with Python

Autoren: Changquan Huang Alla Petukhina

Resource Type: eBook.

Schlagworte: Python (Computer program language), Time-series analysis, Time-series analysis--Forecasting, Time-series analysis--Computer programs

Categories: MATHEMATICS / Probability & Statistics / General, BUSINESS & ECONOMICS / Econometrics, BUSINESS & ECONOMICS / Statistics, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Languages / Python, COMPUTERS / Mathematical & Statistical Software

An Improved Copula‐Based Framework for Efficient Global Sensitivity Analysis.

Autoren: Liu, Hongli Clark, Martyn P. Gharari, Shervan et al.

Quelle: Water Resources Research; Jan2024, Vol. 60 Issue 1, p1-22, 22p

Schlagwörter: SENSITIVITY analysis, GAUSSIAN mixture models, DATA envelopment analysis, PARAMETER estimation

Time Series Analysis with Python Cookbook : Practical Recipes for Exploratory Data Analysis, Data Preparation, Forecasting, and Model Evaluation

Autoren: Tarek A. Atwan

Resource Type: eBook.

Schlagworte: Machine learning, Python (Computer program language)

Categories: COMPUTERS / Data Science / Data Modeling & Design, COMPUTERS / Data Science / Data Warehousing, COMPUTERS / Languages / Python

Software Design for Python Programmers : Principles and Patterns

Autoren: Ronald Mak

Resource Type: eBook.

Categories: COMPUTERS / Languages / Python, COMPUTERS / Programming / Object Oriented, COMPUTERS / Software Development & Engineering / Systems Analysis & Design

Use It or Lose It: Facilitating the Use of Interactive Data Apps in Psychological Research Data Sharing.

Autoren: Usée, Franziska Melzig, Christiane A. Ostwald, Dirk

Quelle: Europe's Journal of Psychology; Aug2024, Vol. 20 Issue 3, p202-219, 18p

Schlagwörter: NATURAL language processing, OPEN scholarship, CLINICAL psychology, PSYCHOLOGICAL research, PYTHON programming language

Text Analysis with Python: A Research Oriented Guide

Autoren: Mamta, Mittal Gopi, Battineni Bhimavarapu, Usharani et al.

Resource Type: eBook.

Schlagworte: Programming languages (Electronic computers), Python (Computer program language), Text processing (Computer science)

Categories: COMPUTERS / Languages / Python, COMPUTERS / Artificial Intelligence / General

Enhancing Cardiac Arrhythmia Detection in WBAN Sensors Through Supervised Machine Learning and Data Dimensionality Reduction Techniques.

Autoren: Hussein, Safa Saad Rashidi, C. B. M. Aljunid, S. A. et al.

Quelle: Mathematical Modelling of Engineering Problems; Dec2023, Vol. 10 Issue 6, p2051-2062, 12p

Schlagwörter: SUPERVISED learning, DATA reduction, ARRHYTHMIA, MACHINE learning, INDEPENDENT component analysis, BODY area networks

Programming models to support data science workflows

Autoren: Ramón-Cortés Vilarrodona, Cristián

Weitere Verfasser: University/Department: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors

Thesis Advisors: Badia Sala, Rosa M. (Rosa Maria), Ejarque Artigas, Jorge

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: Distributed computing, High-performance computing, Data science pipelines, Task-ba workflows, Dataflows, Containers (Computer sicience), COMPSs, PyCOMPSs, AutoParallel, Docker, Àrees temàtiques de la UPC::Informàtica

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/669728
https://dx.doi.org/10.5821/dissertation-2117-330142

Comparative Analysis of AI Models for Python Code Generation: A HumanEval Benchmark Study.

Autoren: Bayram, Ali Menekse Dalveren, Gonca Gokce Derawi, Mohammad

Quelle: Applied Sciences (2076-3417); Sep2025, Vol. 15 Issue 18, p9907, 17p

Schlagwörter: ARTIFICIAL intelligence, PYTHON programming language, COMPARATIVE studies, EVALUATION methodology, BENCHMARK problems (Computer science), GENERATIVE pre-trained transformers, MACHINE learning, COMPUTER software development

Generative AI for Geospatial Analysis: Fine-Tuning ChatGPT to Convert Natural Language into Python-Based Geospatial Computations.

Autoren: Sherman, Zachary Sharma Dulal, Sandesh Cho, Jin-Hee et al.

Quelle: ISPRS International Journal of Geo-Information; Aug2025, Vol. 14 Issue 8, p314, 21p

Schlagwörter: GEOSPATIAL data, LANGUAGE models, PYTHON programming language, GENERATIVE artificial intelligence, GEODATABASES, CHATGPT, SMART cities

Firma/Körperschaft: OPENAI Inc.

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

Autoren: Fachada, Nuno Fernandes, Daniel Fernandes, Carlos M. et al.

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

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

Effect of Deep Recurrent Architectures on Code Vulnerability Detection: Performance Evaluation for SQL Injection in Python.

Autoren: Slotkienė, Asta Poška, Adomas Stefanovič, Pavel et al.

Quelle: Electronics (2079-9292); Sep2025, Vol. 14 Issue 17, p3436, 19p

Schlagwörter: DEEP learning, COMPUTER software security, PYTHON programming language

Leveraging Static Analysis for Feedback-Driven Security Patching in LLM-Generated Code.

Autoren: Alrashedy, Kamel Aljasser, Abdullah Tambwekar, Pradyumna et al.

Quelle: Journal of Cybersecurity & Privacy; Dec2025, Vol. 5 Issue 4, p110, 29p

Schlagwörter: COMPUTER security vulnerabilities, LANGUAGE models, PROGRAM transformation, BENCHMARK problems (Computer science), SOFTWARE maintenance, SOURCE code

Functional Python Programming, 3rd Edition : Use a Functional Approach to Write Succinct, Expressive, and Efficient Python Code

Autoren: Steven F. Lott

Resource Type: eBook.

Schlagworte: Python (Computer program language), Functional programming (Computer science)

Categories: COMPUTERS / Programming / General, COMPUTERS / Programming / Object Oriented, COMPUTERS / Languages / Python

Distinguishing LLM-Generated from Human-Written Code by Contrastive Learning.

Autoren: Xu, Xiaodan Ni, Chao Guo, Xinrong et al.

Quelle: ACM Transactions on Software Engineering & Methodology; May2025, Vol. 34 Issue 4, p1-31, 31p

Schlagwörter: CHATGPT, LANGUAGE models, CODE generators, MACHINE learning

A Systematic Survey on Large Language Models for Code Generation.

Autoren: Jabrw, Sardar K. Sarhan, Qusay I.

Quelle: ARO: The Scientific Journal of Koya University; 2025, Vol. 13 Issue 2, p83-99, 17p

Schlagwörter: LANGUAGE models, CODE generators, PROGRAMMING languages, EVALUATION research, COMPUTER software development, COMPUTER security vulnerabilities, NATURAL language processing