• Suche: Machine Learning For Absolute Beginners

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Development and temporal validation of a deep learning model for automatic fetal biometry from ultrasound videos
Goetz-Fu, M. ; Haller, M. ; Collins, T. ; et al.
In Journal of Gynecology Obstetrics and Human Reproduction December 2025 54(10)

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6

Predictive Modeling for Enhancing MOOC Completion Rates: A Case Study.
Buddhika, Muditha ; Karunarathne, Buddhika ; Nanayakkara, Vishaka
Proceedings of the European Conference on e-Learning (ECEL). 2024, Vol. 23 Issue 1, p43-51. 9p.

Massive open online cour... Higher education Student engagement Deep learning Data mining
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7

AI for Absolute Beginners.
Malik, Sahil
CODE Magazine; May/Jun2019, p8-17, 10p

ARTIFICIAL intelligence ALGORITHMS CENTRAL processing units MACHINE learning COMPUTER programming
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8

Sensor-based machine learning for workflow detection and as key to detect expert level in laparoscopic suturing and knot-tying.
Kowalewski KF ; Garrow CR ; Schmidt MW ; et al.
Publisher: Springer Country of Publication: Germany NLM ID: 8806653 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-2218 (Electronic) Linking ISSN: 09302794 NLM ISO Abbreviation: Surg Endosc Subsets: MEDLINE

Clinical Competence Decision Trees Humans Models, Anatomic Neural Networks, Compute... Ontario …
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9

Monte Carlo methods for absolute beginners
ANDRIEU, Christophe
Advanced lectures on machine learning (Canberra, 2-14 February 2003 ; Tübingen, 4-16 August 2003, revised lectures)Lecture notes in computer science. :113-145

Computer science Informatique Sciences exactes et tech... Exact sciences and techn... Sciences appliquees Applied sciences …
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10

Monte Carlo Methods for Absolute Beginners.
Christophe Andrieu
Advanced Lectures on Machine Learning. :113-145

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11

LasTGL: An Industrial Framework for Large-Scale Temporal Graph Learning
Li, Jintang ; Dan, Jiawang ; Wu, Ruofan ; et al.

Computer Science - Machi... Computer Science - Artif...
Report
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12

Graph Neural Networks in TensorFlow and Keras with Spektral
Grattarola, Daniele ; Alippi, Cesare

Computer Science - Machi... Statistics - Machine Lea...
Report
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13

Graph Neural Networks in TensorFlow and Keras with Spektral [Application Notes]
Grattarola D. ; Alippi C.
IEEE Computational Intelligence Magazine. 16:99-106

FOS: Computer and inform... Computer Science - Machi... Artificial Intelligence Statistics - Machine Lea... 0202 electrical engineer... Machine Learning (stat.M... …
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14

Time Series Data Preparation for CNN and LSTM ; Time Series Data Preparation ; CNN ; LSTM ; Data Preparation for CNN and LSTM
Syed Muhammad Hasanat

Machine learning Deep learning Time Series Data Prepara... Python Time Series Data LSTM …
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15

Comparación de modelos de aprendizaje automático para la predicción de células cancerígenas a partir del complejo MHC I ; Comparison of machine learning models for the prediction of cancer cells from the MHC I complex ; Predicción de células cancerígenas
Navas Luquez, Mateo
OMS, «Cáncer,» 12 septiembre 2018. [En línea]. Available: https://www.who.int/es/news-room/fact-sheets/detail/cancerH ; ASCO, «American Society of Clinical Oncology,» Journal of Clinical Oncology, pp. 212-222, 20 Febrero 2017 ; DANE, «Boletín Técnico,» 20 Diciembre 2019. [En línea]. Available: https://www.dane.gov.co/files/investigaciones/poblacion/bt_estadisticasvitales_IIItr im_2019pr-20-diciembre-2019.pdf ; MinSalud, «PLAN DECENAL PARA EL CONTROL EN COLOMBIA,» 17 Marzo 2012. [En línea]. Available: https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/IA/INCA/plannacional-control-cancer.pdf ; MinSalud, «Cáncer,» Enero 25 2020. [En línea]. Available: https://www.minsalud.gov.co/salud/publica/PENT/Paginas/Prevenciondelcancer.aspx ; A. L. L. T. G. Óscar, «Costos directos de la atención del cáncer,» Cancerol, vol. XX, nº 2, pp. 52-60, 2016 ; J. Greening, «The peptidome comes of age: Mass spectrometry-based characterization of the circulating ....

Antígenos Aprendizaje automático Cáncer Incidencia & prevención... Sistemas Antigen …
Dissertation
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16

Multimodal Approach for Emotion Recognition Based on Simulated Flight Experiments.
César Cavalcanti Roza, Válber ; Adrian Postolache, Octavian
Sensors (14248220). 12/15/2019, Vol. 19 Issue 24, p5516. 1p.

MICROSOFT Corp. EMOTION recognition HUMAN facial recognition... MULTIMODAL user interfac... GALVANIC skin response FLIGHT simulators …
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17

A Tutorial for Exploratory Research: An Eight-Step Approach
Anna Szabelska ; Thomas Victor Pollet ; Olivier Dujols ; et al.

03 medical and health sc... 0302 clinical medicine 4. Education
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19

Comparison of the difference between user and software gradings for the inner distances.
Erik Hallström ; Nikos Fatsis-Kavalopoulos ; Manos Bimpis ; et al.

Genetics Pharmacology Biotechnology Space Science Environmental Sciences n... Biological Sciences not... …
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20

Exploring the Basics of Decision Trees: A Comparative Analysis with Linear Regression
Dr.Shashank Singh,Irfan Abbas ; Mohd.kaif ; Saurabh Kumar ; et al.

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