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61

Artificial Intelligence Predictions in Cyber Security: Analysis and Early Detection of Cyber Attacks
Meaad Ali Khalaf ; Amani Steiti
Babylonian Journal of Machine Learning. 2024:63-68

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62

PYTHON-BASED NEURAL NETWORKS FROM SCRATCH: A HANDS-ON DEEP LEARNING GUIDE
Prof. Dr. KANTHAVEL R ; Dr. DHAYA R ; Dr. ADLINE FREEDA ; et al.

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63

Formation of Bachelor's Skills in the Field of Machine Learning and Intelligent Data Analysis
Marina B. Lapenok ; Lidia G. Shestakova
Scholarly Notes of Transbaikal State University. 19:17-26

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64

NEURAL NETWORKS FROM SCRATCH IN PYTHON
Dr.Dhanusha.C ; Dr. Jayant Bhardwaj ; Dr. A.Purna Chandra Rao ; et al.

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65

Advanced Machine Learning with Python
Hearty, John ; Hearty, John ; Hearty, John ; et al.

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66

Machine Learning Algorithms
Bonaccorso, Giuseppe ; Bonaccorso, Giuseppe ; Bonaccorso, Giuseppe ; et al.

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67

Mastering Python Data Visualization
Raman, Kirthi ; Raman, Kirthi ; Raman, Kirthi ; et al.

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68

Python: Advanced Guide to Artificial Intelligence
Bonaccorso, Giuseppe ; Fandango, Armando ; Shanmugamani, Rajalingappaa ; et al.

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69

Mastering Predictive Analytics with scikit-learn and TensorFlow
Fontaine, Alan ; Fontaine, Alan ; Fontaine, Alan ; et al.

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70

Computación Evolutiva Descentralizada de Modelo Híbrido usando Blockchain y Prueba de Trabajo de Optimización
Consultor de tesis ; Pabón Burbano, María Constanza ; Bastidas Caicedo, Harvey Demian ; et al.
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Huang, "A hybrid stock selection model using genetic algorithms and support vector regression," Applied Soft Computing, vol. 12, p. 807–81, 2012.; E. Levy, "Genetic algorithms and deep learning for automatic painter classification," in conference on Genetic and evolutionary computation - GECCO ’14 , New York, New York, USA, 2014.; E. Levy, "Genetic algorithms and deep learning for automatic painter classification," in Proceedings of the 2014 conference on Genetic and evolutionary computation - GECCO ’14 , New York, New York, USA, 2014.; S. Whiteson, "Evolutionary Function Approximation for Reinforcement Learning," Journal of Machine Learning Research, vol. 8, pp. 877-917, 2006.; R. B. Greve, "Evolving Neural Turing Machines for Reward-based Learning," in Genetic and Evolutionary Computation Conference (GECCO), Denver, Colorado, USA, 2016.; A. Santoro, "One-shot Learning with Memory-Augmented Neural Networks," Cornell University , Ithaca, NY, USA, 2016.; D. Izzo, "The generalized isalnd model," Studies in Computational Intelligence, vol. 415, pp. 151-169, 2012.; G. Folino, "P-CAGE: An Environment for Evolutionary Computation in Peer-to-Peer Systems," in European Conference on Genetic Programming, Berlin, 2006.; A. L. Ian Scriven, "Decentralised distributed multiple objective particle swarm optimisation using peer to peer networks," in IEEE World Congress on Evolutionary Computation, 2008. CEC 2008, 2008.; A. L. C. Fernando Silva, "odNEAT: An Algorithm for Decentralised Online Evolution of Robotic Controllers," Evolutionary Computation , vol. 23, no. 3, pp. 421-449, 2015.; D. Jakobović, "ECF - Evolutionary Computation Framework," University of Zagreb,; M. A. García-Sánchez P., "A Methodology to Develop Service Oriented Evolutionary Algorithms," Intelligent Distributed Computing VIII, vol. 570, 2015.; S. Cahon, "ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics," Journal of Heuristics, vol. 10, no. 3, pp. 357-380, 2004.; D. R. White, "Software review: the ECJ toolkit," Genetic Programming and Evolvable Machines, vol. 13, no. 1, pp. 65-67, 2011.; M. G. Arenas, "A Framework for Distributed Evolutionary Algorithms," Lecture Notes on Computer Science, vol. 2439, pp. 665-675, 2002.; J. L. J. Laredo, "Resilience to churn of a peer-to-peer evolutionary algorithm," International Journal of High Performance Systems Architecture, vol. 1, no. 4, pp. 260-268, 2008.; C. Rohrs, "Query Routing for the Gnutella Network," Lime Wire LLC, 2002.; R. Fielding, "Chapter 5: Representational State Transfer (REST)," in Architectural Styles and the Design of Network-based Software Architectures, Irvine, Ca, University of California, 2000.; P. C. R. K. Len Bass, Software Architecture in Practice - Second Edition, Addison Wesley, 2003.; S. 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Liang, "Evolving Deep Neural Netwokrs," eprint arXiv:1703.00548, 2017.; Reponame:Vitela: Repositorio Institucional PUJ; Instname:Pontificia Universidad Javeriana Cali

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71

Hands-On Industrial Internet of Things
Veneri, Giacomo ; Capasso, Antonio ; Veneri, Giacomo ; et al.

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72

Automating the assessment of multicultural orientation through machine learning and natural language processing.
Goldberg, Simon B. ; Tanana, Michael ; Stewart, Shaakira Haywood ; et al.
Psychotherapy: Theory, Research & Practice; Psychotherapy: Theory, Research, Practice, Training

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75

Desarrollo de un sistema de percepción para detección de carril y generación de trayectorias para vehículos autónomos
Correa Sandoval, José Miguel ; Díaz Zapata, Manuel Alejandro ; Perafán Villota, Juan Carlos ; et al.
instname:Universidad Autónoma de Occidente ; reponame:Repositorio Institucional UAO ; [1] S. P. Narote, P. N. Bhujbal, A. S. Narote, and D. M. Dhane, “A review of recent advances in lane detection and departure warning system,” Pattern Recognit., vol. 73, pp. 216–234, 2018. [2] El Tiempo, “Producción de petróleo bajó en 2017 en Colombia,” Periodico El Tiempo, [En línea]. Disponible en: https://www.eltiempo.com/economia/sectores/produccion-de-petroleo-bajo- en-2017-en-colombia-171848. [3] P. Tientrakool, Y. C. Ho, and N. F. Maxemchuk, “Highway capacity benefits from using vehicle-to-vehicle communication and sensors for collision avoidance,” IEEE Veh. Technol. Conf., pp. 1–5, 2011. [4] D. Muoio, “19 companies racing to put ....

Ingeniería Mecatrónica Vehículos autónomos Visión por computador Simulación por computado... Seguimiento de carril Autonomous vehicles
Dissertation
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77

An integrated model of semantics and control.
Giallanza, Tyler ; Campbell, Declan ; Cohen, Jonathan D. ; et al.
Psychol Rev

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78

Identifying resource-rational heuristics for risky choice.
Krueger, Paul M. ; Callaway, Frederick ; Gul, Sayan ; et al.
Psychol Rev

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79

Physiological regulation processes differentiate the experience of ruptures between patient and therapist.
Tchizick, Amit ; Kleinbub, Johann Roland ; Bittan, Shahar ; et al.
Psychotherapy: Theory, Research & Practice; Psychotherapy: Theory, Research, Practice, Training

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80

A computational model of aesthetic value.
Brielmann, Aenne A. ; Dayan, Peter
Psychol Rev

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