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NouraAbuthnain/README.md

Hi, I’m Noura Abuthnain 👋

I have a Computer Science background with experience in machine learning and deep learning, including work in natural language processing and computer vision. My interests focus on applied, data-driven AI systems and understanding how different models behave when applied to real datasets.

My work involves model comparison, experimentation, and evaluation of learning-based systems. I also have experience translating technical ideas into clear, usable implementations, informed by additional experience in UX/UI design and frontend–backend development.

💻 Technologies:

  • Python, HTML, CSS, JavaScript, Dart
  • PyTorch, TensorFlow, Keras
  • React, React Native, Next.js, Flutter
  • Flask, Node.js, Firebase, MongoDB, MySQL
  • Figma, Adobe Illustrator, UX/UI Design, FlutterFlow
  • Git, GitHub

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  1. convolutional-autoencoder-anomaly-detection convolutional-autoencoder-anomaly-detection Public

    Convolutional autoencoders trained on normal data, with an attention-enhanced model and Gradio-based deployment, are used to detect anomalies in images.

    Jupyter Notebook

  2. cnn-skin-lesion-classification cnn-skin-lesion-classification Public

    Skin lesion classification using CNNs and transfer learning (ResNet50) on the HAM10000 dataset.

    Jupyter Notebook

  3. arabic-text-classification-summarization arabic-text-classification-summarization Public

    Arabic NLP project comparing traditional, deep learning, and transformer-based models for text classification and summarization.

    Jupyter Notebook 1

  4. AryafAlotaibi/Income-Prediction-Using-Machine-Learning-Models AryafAlotaibi/Income-Prediction-Using-Machine-Learning-Models Public

    For a more detailed implementation, please refer to the pdf file

    Python

  5. zainahm5/Web- zainahm5/Web- Public

    EJS 1

  6. sarah4-k/Trove sarah4-k/Trove Public

    Dart