Data Science & AI/ML enthusiast
I focus on turning data into clear, actionable insight through rigorous analysis and machine learning. My work is grounded in strong fundamentals, methodology and real-world application. I help people reduce uncertainty, uncover patterns, and make better decisions using evidence-driven systems.
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A CS student and Python developer with a focused interest in Data Science and Artificial Intelligence, working at the intersection of data, algorithms, and real-world problem solving. My credibility comes from hands-on project experience—building machine learning models, data pipelines, and API-driven systems using tools like Python, Pandas, NumPy, Scikit-learn, FastAPI, and Flask—where I emphasize correctness, reproducibility, and interpretability over shortcuts. I'm deeply passionate about understanding how models learn, how data behaves, and how insights translate into decisions, especially in applied domains such as prediction, automation, and intelligent monitoring systems.
What I bring is the ability to turn unstructured or noisy data into structured insights and deployable solutions, helping individuals and teams reduce uncertainty, improve decision-making, and build systems that are both technically sound and practically useful.
As I continue learning, I actively work on projects, study open-source implementations, and explore new ideas in AI and machine learning to strengthen both my technical and problem-solving abilities.
Artificial Intelligence and Machine Learning sub-sections.
Coordinated and monitored the server. Guided participants in completing tasks.
Overseed and ensured proper conduct in the community. Provided group updates and prompted discussion topics in technology, culture and personal growth.
Developed and maintained Flask-based web applications, improving feature delivery and bug resolution.
Collaborated with senior developers in code reviews, ensuring maintainable and efficient solutions.
Contributed to new feature development, resulting in faster project delivery.
Built and maintained FastAPIs that served data to multiple client applications. Prepared daily reports and participated in mentoring sessions.
Prepared learning material for students. Experimental and practical design.
Learner's seminar co-organizer. Helped learners in precision and accurate recording.
Gained experience in Organizational Skills, Accountability, Teamwork, and Laboratory Safety.
Customer relationship building. Agile business, giving priority to clients needs and satisfaction.
Entrepreneurial Spirit.
MatXSense – AI Digital Twin for Material Degradation. Material degradation monitoring using virtual IoT sensors and machine learning. Predict health, remaining useful life (RUL), and degradation risk for steel, concrete, polymers, and aluminum in different environments—with a bridge digital twin and optional sensor-driven inference.
Interactive dashboard for visualizing complex datasets with real-time updates and custom reporting.
Optimized bulk email tool delivery tool for sending personalized HTML-based emails that achieved an 80% delivery success rate for over 2000 users.
Automated the process using Jinja2 templates and environmental variables for security.
Utilized a CSV file to manage recipient data/details.
Implemented an algorithm to read codes from file or webcam.
Decoded QR codes and barcodes using OpenCV and pyzbar.
Preprocessed the image(optional resizing + grayscale) for accuracy. Utilized the Pandas Dataframe for decoded results storage.
Location: Algiers, Algeria
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