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natek-1/README.md

👋 Hi, I'm Nathan Gabriel Kuissi

🎓 About Me I'm a second-year Data Science student at the University of Waterloo, passionate about transforming data into actionable insights. My areas of interest include machine learning, deep learning, computer vision, and natural language processing.

💻 Technical Skills

  • Programming Languages: Python, R
  • Frameworks & Libraries: scikit-learn, PyTorch, TensorFlow, Pandas
  • Tools: Docker, GitHub Actions, AWS
  • Practices: Continuous Integration (CI), Continuous Deployment (CD)

🔍 What I'm Looking For

  • Internship Opportunities: I'm eager to apply my skills in a practical setting and contribute to innovative projects.
  • Research Collaborations: Interested in collaborating on cutting-edge research in AI and data science.

🌱 Current Projects I'm currently working on projects involving computer vision applications and enhancing NLP models to better understand human language.

📫 Get in Touch Feel free to reach out for collaboration or if you're looking for a motivated intern or research assistant:

Thank you for visiting my profile!

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  1. Image-Captioning Image-Captioning Public

    This project implements the "Show, Attend and Tell" model for generating descriptive captions for images using a neural network with visual attention

    Jupyter Notebook

  2. Image-search-engine-model-training Image-search-engine-model-training Public

    Front end application for my image search engine project. Small micro service app.

    Python

  3. finance_complaint_analysis finance_complaint_analysis Public

    Using government dataset to make predictions about finance related complains by customers using ML, NLP application built with airflow

    Jupyter Notebook

  4. Chest-CT-Scan-Classification Chest-CT-Scan-Classification Public

    Chesss Disease classification using Tensorflow, MLFLOW, Data Version Control and Jenkins

    Jupyter Notebook

  5. Forest-Covertype Forest-Covertype Public

    Classification of pixels into 7 forest cover types based on attributes such as elevation, aspect, slope, hillshade, soil-type. Application created using Flask, Docker, MongoDB and AWS S3

    Jupyter Notebook