app developer, front and backend, work ml and dl models

aya boumaiza

app developer, front and backend, work ml and dl models

Available to hire

app developer, front and backend, work ml and dl models

Work Experience

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Education

master data science at university constantine2 algeria
May 11, 2025 - June 17, 2025
data science studant

Qualifications

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Industry Experience

Software & Internet
    paper cyber attack detections
    This project focuses on building a machine learning system to detect cyber attacks on IoT (Internet of Things) networks. The goal is to identify abnormal behavior or malicious activities in real-time to enhance the security of connected devices. Key Steps and Features: Data Preprocessing: Cleaned and handled missing values, duplicates, and noise in the raw IoT network traffic data Encoded categorical features and normalized numerical data for model readiness Exploratory Data Analysis (EDA): Visualized attack types, class imbalance, and feature distributions Identified key features that influence cyber attack detection Model Training and Evaluation: Tested multiple machine learning models (e.g., Random Forest, SVM, KNN, Logistic Regression) Evaluated models using accuracy, precision, recall, and F1-score Performed train/test split and cross-validation for robust performance
    uniE621 data visualization
    This project focuses on analyzing and visualizing cyber attack data targeting IoT (Internet of Things) devices using Power BI. The main goal is to detect patterns, monitor threat levels, and provide insights into the types, frequency, and sources of attacks on IoT networks.
    uniE608 bloody lab
    Description: This is a responsive web application developed for a data analysis laboratory, designed to manage and streamline the workflow between different users: Admin General (super admin), Doctor/Laboratory Specialist, and Client. The platform allows secure communication, report management, and data visualization within the laboratory environment. Multi-user System: Admin General: Full control over users, lab tests, reports, and platform settings. Doctor/Laborant: Upload and analyze test results, generate reports, and manage patient data. Client: Access their own test results and reports securely. Technologies Used: Frontend: HTML5, CSS3, JavaScript, Bootstrap for responsive and clean UI design. Backend: Django (Python) for server-side logic, authentication, and database management.

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