ELIZ HABIBOULLAH Software Engineer • Machine Learning Enthusiastic

Meet Me

Professional Me

As a dedicated Software Engineer with extensive expertise in Machine Learning, I bring a strong foundation in both theoretical research and practical implementation to academic research challenges. Having completed my degree in Computer Science with Honours in Software Engineering from City University of Malaysia, I have developed considerable proficiency in ML methodologies and their research applications.

I have hands-on experience with a wide range of machine learning techniques, spanning supervised learning, unsupervised learning, deep learning, reinforcement learning, and optimization algorithms. My work includes developing advanced predictive models, clustering algorithms, anomaly detection, and reinforcement learning systems. I have also worked extensively with neural networks and natural language processing, alongside model optimization with containerization for real-world cloud deployment, creating scalable environments for reproducible research.

My research interests span AI, machine learning, computer vision, cyber-physical systems, quantum computing, NLP, and robotics.

I am actively seeking research opportunities in these areas.

Languages

My favorite languages for software engineering and machine learning.

ML F/W & L

Tensorflow Logo pytorch Logo Scikit_learn Logo Keras Logo

My Go-To Frameworks and Librarys for Designing, Developing, Training, and Deploying ML Models

Full Stack

My preferred technologies for full stack web programming and database architecture.

Go-To Tools

Keras Logo

My favorite tools for version control, code editing, and container orchestration.

Featured Projects

Personal Website

Personalized Product Recommendation System for Marsaty

   

Developed a machine learning-based recommendation system to personalize product suggestions for users on the Marsaty platform. The system analyzes customer behavior to generate tailored product recommendations, enhancing the shopping experience and boosting user engagement.

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Perpetual Crusades

Neural Network SMS Text Classifier

   

Built an SMS text classifier using neural networks to automatically detect and filter out spam messages. This project was developed during my training at FreeCodeCamp for the Machine Learning with Python Certification. The classifier processes text messages and categorizes them as either spam or legitimate, improving the efficiency of communication.

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COVID-19 Tracker App

NLP-Powered Chatbot

     

Designed and developed a custom chatbot using Python and NLP technologies to enhance customer support. Implemented sentiment analysis to better understand feedback and improve response accuracy, leading to more effective interactions and higher customer satisfaction.

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Valuto: Account Management System
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Full Stack Web App

       

Created a full-stack comprehensive SaaS solution that integrates multiple vendors, streamlines operations, and automates tasks. The platform allows seamless product listing, customer targeting, and order management, offering exponential growth opportunities for businesses of all sizes.

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