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BA@boumaizaaya
Data scientist skilled in machine learning and deep learning techniques.
AlgeriaI am a passionate data scientist with a Master's Degree in Data Science from the University of Constantine 2. My journey in the field has been marked by a strong focus on machine learning and deep learning applications, particularly in the realm of healthcare and cybersecurity. I have developed innovative models that not only detect cyberattacks on IoT devices but also analyze product reviews on Amazon, showcasing my versatility in handling diverse datasets.
Throughout my academic career, I have successfully built platforms that enhance user experience and data management. For instance, I created a web platform for laboratory analysis that allows doctors to upload test results securely while providing clients with easy access to their reports. My work on synthetic data generation, including the development of Conditional GANs and Variational Autoencoders, demonstrates my commitment to advancing the field of data science through practical applications.
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Work history, roles, and key accomplishments
Academic & Personal Projects
Built a cGAN model to generate high-quality tabular data for Mesothelioma diagnosis, trained to reflect class distribution and correlations. Implemented a Conditional Variational Autoencoder (cVAE) to generate synthetic CT images for brain stroke, focusing on learning disease-specific features.
Academic & Personal Projects
Built a platform where doctors upload test results, clients view reports, and admins manage users and lab tests securely. Developed and trained a Conditional GAN to generate realistic tabular data for Alzheimer's patients, ensuring synthetic data preserved statistical properties.
Academic & Personal Projects
Developed a machine learning model to detect cyberattacks on IoT devices and visualized security insights using Power BI for better threat analysis. Built a deep learning model (RNN) to analyze Amazon product reviews using Python.
Academic & Personal Projects
Created a full-stack web platform for synthetic data generation, allowing users to select diseases and specify data parameters. The system utilizes pre-trained models on the backend to automate the data generation process.
Degrees, certifications, and relevant coursework
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