Comprehensive collection of references, publications, courses, and evidence supporting my skills and projects.
Research focusing on the development of efficient algorithms for predicting the trajectories of celestial bodies with applications in space mission planning.
Journal of Computational Astrophysics, Vol. 28, Issue 3, 2022
View on arXivNovel approach for optimizing convolutional neural networks specifically designed for processing and analyzing astronomical imagery from various space telescopes.
IEEE Transactions on Computational Intelligence, 2023
View on IEEEExploration of quantum computing principles and their applications in modern cryptographic systems, with focus on post-quantum cryptography.
International Journal of Quantum Information, 2021
View JournalDetailed documentation of the deep learning model for classifying astronomical objects from telescope imagery, including methodology, data preprocessing techniques, and validation results.
View RepositoryTechnical documentation and user guide for the quantum algorithm simulator, explaining the implementation of quantum gates, circuits, and simulation methodology.
View RepositoryComprehensive documentation of the mathematical modeling framework, including API reference, usage examples, and performance benchmarks.
View RepositoryMaster's Degree with focus on computational methods and mathematical modeling.
University of Mathematics and Computational Sciences, 2020
Professional certification in TensorFlow development, validating skills in building deep learning models with TensorFlow.
Google, 2021
Certification DetailsComprehensive specialization covering advanced topics in data science, machine learning, and statistical analysis.
IBM, 2022
Program DetailsResources and references for programming languages I'm proficient in.
Python: Official Documentation
Rust: The Rust Programming Language
C++: ISO C++ Standards
JavaScript: MDN Web Docs
Resources for data science and machine learning frameworks and methodologies.
TensorFlow: API Documentation
PyTorch: Documentation
Scikit-learn: User Guide
References for mathematical concepts and algorithmic implementations.
Linear Algebra: MIT OpenCourseWare
Algorithms: Princeton University Algorithms
Quantum Computing: Qiskit Documentation
Portfolio of over 160 completed programming projects spanning various domains including data science, web development, machine learning, and scientific computing.
GitHub PortfolioContributions to various open-source projects, particularly in scientific computing and data science libraries.
Contribution HistoryProfessional experience in research and development roles, focusing on algorithm optimization and mathematical modeling for real-world applications.
Source code repositories, contributions, and projects.
github.com/K11E3RProfessional profile, experience, and connections.
linkedin.com/in/yassine-naananiAcademic and project profile at Zone01 Normandie.
Zone01 Normandie ProfileProfessional activities and contributions under the YNA identifier.
Development work and contributions under the K11E3R identifier across various platforms.
GitHubCitations and academic publications under Yassine Naanani in scholarly databases.
Google Scholar ResearchGateContributions to technical forums, discussions, and communities.
Stack Overflow Dev.to MediumParticipation in data science and AI communities, forums, and discussions.
KaggleContributions to various open source projects under Yassine Naanani, YNA, and K11E3R identifiers.
GitHub Projects GitHub MentionsLive demonstrations, case studies, and project showcases across various platforms.
Project PortfolioTechnical articles, blog posts, and publications authored by or mentioning Yassine Naanani.
Dev.to Articles Medium ArticlesMentions and references in industry and academic publications, papers, and reports.
Academic CitationsParticipation in technical conferences, meetups, and events as presenter, attendee, or contributor.
Participation in hackathons, code challenges, and competitive programming events.