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himelds/README.md
Himel Das - Banner

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🧑‍💻 About Me

I hold an MSc in Applied Artificial Intelligence and Data Analytics from the University of Bradford, UK, and I work at the intersection of machine learning, advanced analytics, and real-world problem solving.

My focus is on building intelligent, end-to-end solutions — from exploratory data analysis and feature engineering through to model development and business reporting. I've built predictive models achieving R² = 0.94, analysed over 1.8M records to uncover patterns that inform policy, and designed full-stack data applications from the ground up.

I'm drawn to problems where data can change how decisions are made — and I bring a rigorous analytical mindset, clean engineering practices, and genuine curiosity to every challenge.

🛠️ Tech Stack & Tools

👨‍💻 Languages 🤖 ML & AI 🧰 Tools & Platforms

Matplotlib Seaborn Plotly Power BI Pandas NumPy Streamlit Excel

🎓 Education

🎓 University of Bradford, UK
Master of Science — Applied Artificial Intelligence and Data Analytics
Modules: Machine Learning, Big Data Visualization, Business Analytics
🎓 University of Science and Technology Chittagong, BD
Bachelor of Science Engineering — Electrical and Electronic Engineering

⭐ If you find my work helpful, consider starring my repos!

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  1. London_Bike_Sharing_Project London_Bike_Sharing_Project Public

    Developed an end-to-end machine learning pipeline and interactive Streamlit Dashboard to predict demand for London's bike-sharing system.

    Jupyter Notebook

  2. Analysis_of_United_Kingdom_Traffic_Accidents Analysis_of_United_Kingdom_Traffic_Accidents Public

    Analyzed large-scale UK traffic accident data to identify key factors influencing accident frequency and severity using data visualization and statistical analysis.

    Jupyter Notebook

  3. Solar-Flare-Classification-Using-Machine-Learning Solar-Flare-Classification-Using-Machine-Learning Public

    Developed a robust MLOps pipeline to classify solar flare intensity using historical data, handling severe class imbalance with SMOTE and utilizing SHAP for feature analysis.

    Jupyter Notebook

  4. ADEGuard ADEGuard Public

    ADEGuard: An AI-powered NLP system for detecting and classifying Adverse Drug Events (ADEs) from VAERS reports using BioBERT and symptom clustering.

    Jupyter Notebook

  5. Expense-Management-System Expense-Management-System Public

    A full-stack Expense Tracking System built with FastAPI backend and Streamlit frontend. Helps users track, categorize, budget, and analyze their expenses with an interactive dashboard and clean UI.

    Python

  6. Business-360-insight Business-360-insight Public

    Developed an interactive Power BI dashboard to deliver data-driven insights across multiple business functions, enabling informed decision-making and performance analysis.