• Suche: Python 3 for Machine Learning

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202

To Control Diabetes Using Machine Learning Algorithm and Calorie Measurement Technique.
Viveka, T. ; Columbus, C. Christopher ; Velmurugan, N. Senthil
Intelligent Automation & Soft Computing; 2022, Vol. 33 Issue 1, p535-547, 13p

MACHINE learning CALORIC content of foods MEALS BLOOD sugar DEEP learning K-nearest neighbor class... …
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203

Deep Learning-Based HLA Allele Imputation Applicable to GWAS
Tatsuhiko, Naito
Methods in Molecular Biology ISBN: 9781071638736

Deep Learning HLA Antigens Humans Computational Biology Polymorphism, Single Nuc... Alleles …
Buch
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204

Mastering Geospatial Analysis with Python
Toms, Silas ; Rees, Eric Van ; Crickard, Paul ; et al.

E-Ressource
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205

APNet, an explainable sparse deep learning model to discover differentially active drivers of severe COVID-19.
Gavriilidis, George ; Vasileiou, Vasileios ; Dimitsaki, Stella ; et al.
Bioinformatics. 41(3)

COVID-19 Humans Deep Learning SARS-CoV-2 Proteomics Computational Biology
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206

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207

Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation.
Liu M ; Grinberg Dana A ; Johnson MS ; et al.
Publisher: American Chemical Society Country of Publication: United States NLM ID: 101230060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-960X (Electronic) Linking ISSN: 15499596 NLM ISO Abbreviation: J Chem Inf Model Subsets: MEDLINE

Kinetics Machine Learning Cheminformatics Software
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208

Machine learning based on Hawkes processes and stochastic optimization
Apprentissage automatique avec les processus de Hawkes et l'optimisation stochastique
Bompaire, Martin ; Centre de Mathématiques Appliquées de l'Ecole polytechnique (CMAP) ; Institut National de Recherche en Informatique et en Automatique (Inria)-École polytechnique (X) ; et al.
Other Statistics [stat.ML]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLX030⟩

Open source Causality Stochastic optimization Hawkes processes Logiciel libre Causalité …
Dissertation
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209

Organization of a Hybrid Multi-Platform Online Course on 'Machine Learning' for Higher Education System
A. A. Nikandrov ; X. R. Piotrowska
Prepodavatel XXI vek. :110-127

0301 basic medicine 03 medical and health sc... 4. Education 05 social sciences 0503 education
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210

Hands-On Image Processing with Python
Dey, Sandipan ; Dey, Sandipan ; Dey, Sandipan ; et al.

E-Ressource
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211

Benchmarking Autonomous Scattering Experiments Illustrated on TAS
Teixeira Parente, Mario ; Schneidewind, Astrid ; Brandl, Georg ; et al.
Frontiers in Materials. 8

4006 Communications Engi... 40 Engineering (for-2020... Machine Learning and Art... autonomous experiment data-driven analysis cost-benefit analysis …
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213

Análise de sentimentos sobre as vacinas contra covid-19: um estudo com algoritmo de machine learning em postagens no twitter
Rodas, Cecilio Merlotti ; Barros , Suellen Elise Timm ; Souza, Rodrigo Ananias da Silva ; et al.
Revista de Saúde Digital e Tecnologias Educacionais; v. 7 n. 3 (2022): Edição especial 3 - VI Seminário Internacional de Informação para a Saúde; 24-44 ; 2525-9563 ; 10.36517/resdite.v7i3

Análise de sentimento Covid-19 Vacina Twitter Machine Learning
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214

MAM-STM: A software for autonomous control of single moieties towards specific surface positions.
Ramsauer, Bernhard ; Cartus, Johannes J. ; Hofmann, Oliver T.
Computer Physics Communications. Oct2024, Vol. 303, pN.PAG-N.PAG. 1p.

MACHINE learning SCANNING probe microscop... SCANNING tunneling micro... REINFORCEMENT learning EXPERT systems PYTHON programming langu... …
Zeitschrift
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215

A robust synthetic data generation framework for machine learning in high-resolution transmission electron microscopy (HRTEM)
Rangel DaCosta, Luis ; Sytwu, Katherine ; Groschner, CK ; et al.
npj Computational Materials. 10(1)

Engineering Materials Engineering Machine Learning and Art... Bioengineering Data Science Biomedical Imaging …
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216

Reescribir Slatt en python3 ; Rewrite Slatt in python 3
Martínez Floranes, Alejandro ; Gómez Pérez, Domingo ; Universidad de Cantabria

reglas de asociación hipergrafos Slatt refactorizar association rules hypergraph …
Dissertation
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217

A comparison of the response-pattern-based faking detection methods.
Nie, Weiwen ; Hernandez, Ivan ; Tay, Louis ; et al.
J Appl Psychol

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218

PyLEnM: A Machine Learning Framework for Long-Term Groundwater Contamination Monitoring Strategies
Meray, Aurelien O ; Sturla, Savannah ; Siddiquee, Masudur R ; et al.
Environmental Science and Technology. 56(9)

Hydrology Earth Sciences Networking and Informati... Machine Learning and Art... Environmental Monitoring Groundwater …
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219

Machine learning model with a novel self–adjustment method: A powerful tool for predicting biomass ash fusibility and enhancing its potential applications.
Mu, Lin ; Wang, Zhen ; Sun, Meng ; et al.
Renewable Energy: An International Journal. Dec2024:Part A, Vol. 237, pN.PAG-N.PAG. 1p.

Manufacturing processes Biomass conversion Machine learning Aluminum oxide Research personnel Investors
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220

Step 1: Getting Started in Python 3
Swamynathan, Manohar
Mastering Machine Learning with Python in Six Steps ; page 1-64 ; ISBN 9781484249468 9781484249475

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