• Suche: Building Machine Learning Systems with Python

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101

Symbolic DNN-Tuner: A Python and ProbLog-based system for optimizing Deep Neural Networks hyperparameters
Michele Fraccaroli ; Evelina Lamma ; Fabrizio Riguzzi
SoftwareX, Vol 17, Iss , Pp 100957- (2022)

Deep learning Probabilistic Logic Prog... Hyper-parameters tuning Neural-symbolic integrat... Computer software QA76.75-76.765
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102

Solutions for Modelling the Marine Oil Spill Drift.
Popa, Catalin ; Atodiresei, Dinu ; Toma, Alecu ; et al.
Environments (2076-3298); Apr2025, Vol. 12 Issue 4, p132, 25p

SATELLITE-based remote s... MACHINE learning VERTICAL mixing (Earth s... MARINE pollution PARTIAL differential equ... DEEP learning …
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103

JANC: A cost-effective, differentiable compressible reacting flow solver featured with JAX-based adaptive mesh refinement
Wen, Haocheng ; Luo, Faxuan ; Xu, Sheng ; et al.
In Computer Physics Communications February 2026 319

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104

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105

A Novel Approach for Optimizing Building Energy Models Using Machine Learning Algorithms.
Kubwimana, Benjamin ; Najafi, Hamidreza
Energies (19961073). Feb2023, Vol. 16 Issue 3, p1033. 16p.

MELBOURNE (Vic.) FLORIDA Institute of Tec... MACHINE learning GLOBAL optimization PYTHON programming langu... GENETIC algorithms …
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106

Indoor occupancy detection and counting system based on boosting algorithm using different sensor data.
Kumari, Pushpanjali ; Reddy, S. R. N. ; Yadav, Richa
Building Research & Information. Jan/Feb2024, Vol. 52 Issue 1/2, p87-106. 20p.

BOOSTING algorithms MACHINE learning MOTION detectors SUPPORT vector machines FEATURE extraction DETECTORS
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107

Digital Urban Twins for heavy rain events - An open source QGIS plugin for machine learning classification of residential buildings using CityGML with additional datasets.
Bong, Alexander ; Clemen, Christian
ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences; 9/2/2025, Vol. 10 Issue 4/W6, p25-32, 8p

DRESDEN (Germany) GERMANY DIGITAL twin CLASSIFICATION algorithm... HYDROLOGIC models DWELLINGS …
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108

Deep Learning and Market Trends: Building Future Economic Forecasting Models.
Pang, MaoQian
International Journal of High Speed Electronics & Systems. Dec2024, p1. 19p.

ECONOMIC forecasting ECONOMIC indicators ECONOMIC models LONG short-term memory OPTIMIZATION algorithms DEEP learning
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109

DEVELOPMENT OF A ROUTING METHOD FOR GROUND-AIR AD-HOC NETWORK OF SPECIAL PURPOSE.
Bieliakov, Robert
Technology Audit & Production Reserves; 2024, Vol. 2 Issue 2(76), p44-51, 8p

BIT error rate TELECOMMUNICATION system... REINFORCEMENT learning MACHINE learning COMPUTATIONAL complexity ROUTING algorithms …
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110

Machine learning Models Compositions Builder
Domashova, Jenny ; Norkina, Anna ; Kosvintsev, Kirill ; et al.
In Procedia Computer Science 2022 213:157-164

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111

Troubleshooting Python deep learning
Packt Publishing, production company. ; Konczyk, Jakub, author, speaker.

Video
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112

pyCHARMM: Embedding CHARMM Functionality in a Python Framework
Buckner, Joshua ; Liu, Xiaorong ; Chakravorty, Arghya ; et al.
Journal of Chemical Theory and Computation. 19(12):3752-3762

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113

IMDB Sentiment Analysis Based on Comment by Using Machine Learning.
TARANI, MAMIDI ; DURGAPRASAD, KURMAPU
International Scientific Journal of Engineering & Management; Jul2025, Vol. 4 Issue 7, p1-9, 9p

MACHINE learning NATURAL language process... NAIVE Bayes classificati... FILM reviewing CUSTOMER feedback SENTIMENT analysis
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114

TrueLearn: A Python Library for Personalised Informational Recommendations with (Implicit) Feedback
Qiu, Yuxiang ; Djemili, Karim ; Elezi, Denis ; et al.

Computer Science - Infor... Computer Science - Artif... Computer Science - Compu... Computer Science - Machi... Statistics - Machine Lea... H.3.3 …
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115

Modelação e simulação computacional de exercícios de evacuação da Escola Secundária Rainha Dona Leonor, Lisboa
Lucas, Omar Alexandre

Python Machine learning Simulação -- Simulation... Modelos baseados em agen... Sistemas de informação g... Bibliotecas …
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116

The show must go on: a reliability assessment platform for resistive random access memory crossbars.
Pelke, Rebecca ; Staudigl, Felix ; Thomas, Niklas ; et al.
Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences; 1/16/2025, Vol. 383 Issue 2288, p1-15, 15p

NONVOLATILE random-acces... TECHNOLOGICAL innovation... COMPUTING platforms MACHINE learning SYSTEM integration
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117

Want to Build an AI System? Use These Languages and Frameworks.
Balakrishnan, S.
Open Source For You; Apr2023, Vol. 11 Issue 6, p59-62, 4p

OPEN source software PROGRAMMING languages JAVASCRIPT programming l... MACHINE learning ARTIFICIAL intelligence PYTHON programming langu...
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118

Machine learning for visible light positioning with non-imaging sensors
Rocha, Renato Samuel Oliveira Barros

Visible light positionin... Indoor positioning syste... Positioning with photodi... Non imaging sensors Machine learning Positioning with machine...
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119

lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systems
Sedler, Andrew R. ; Pandarinath, Chethan

Computer Science - Machi... Quantitative Biology - N...
Report
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120

Transforming Building Energy Management: Sparse, Interpretable, and Transparent Hybrid Machine Learning for Probabilistic Classification and Predictive Energy Modelling
Yiping Meng ; Yiming Sun ; Sergio Rodriguez ; et al.
Architecture, Vol 5, Iss 2, p 24 (2025)

hybrid machine learning sparse interpretable tra... energy prediction uncertainty quantificati... sustainable energy manag... Architecture …
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