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sorna-fast/README.md

πŸ‘‹ Hello, I'm Masoud Ghasemi

Backend and AI Developer implementing scalable APIs, database management, and developing robust architectures using Python. Proven track record in building machine learning models with over 98% accuracy in image processing and medical diagnostics, utilizing TensorFlow, Keras, and Scikit-learn. Eager to collaborate in innovative teams to develop intelligent and scalable systems in the fields of data analytics and backend services.

🧠 Skills, Activities & More

  • Backend Development: Practical experience with Django, Django REST Framework, FastAPI, and more β€” including scalable APIs, admin panels, and workflow automation.

django logo fastapi logo sqlalchemy logo jquery logo

  • Data Analysis, Machine Learning & Deep Learning: Hands-on projects using Pandas, Scikit-Learn, TensorFlow, and more. I’ve worked on regression, classification, clustering, and convolutional neural networks (CNNs) for tasks like prediction, segmentation, and image recognition.

aiscript logo scikit-learn logo tensorflow logo numpy logo pandas logo

  • Scripting & Databases: Skilled in writing scripts and queries using SQL and NoSQL. I’ve designed normalized schemas and automated tasks such as data entry, backups, and scheduled reporting.

sqlite logo mysql logo postgresql logo microsoftsqlserver logo mongodb logo

πŸŽ“ Education & Certifications


✨ Completed the Django Master Course from Python Master.

πŸš€ Currently progressing through the Artificial Intelligence Master Course β€” expected to finish by semester six.

πŸ“š I’m committed to continuous learning and skill development, and I’m actively following semesters 7 and 8.

πŸ“¬ Contact

πŸ“œ Licensing & Ownership


All projects, documentation, and more in this repository are created and maintained by me. Licensing is customized for each project to ensure proper protection of intellectual property and reputation. For commercial use or collaboration, please contact me directly.

Pinned Loading

  1. tb-chest-xray-classifier tb-chest-xray-classifier Public

    TB Chest X-Ray Classifier - Deep learning model for Tuberculosis detection using CNN architecture with 99.5% accuracy and 0.999 AUC score.

    Jupyter Notebook 2 1

    72E5
  2. rock-paper-scissors-cnn rock-paper-scissors-cnn Public

    About A complete CNN image classification system that accurately identifies hand gestures for rock, paper, and scissors. Features custom neural architecture, data augmentation, and 99% validation a…

    Jupyter Notebook 2

  3. media-database-cs50sql media-database-cs50sql Public

    Final project for CS50 SQL – A normalized media database to manage movies, series, contributors, users, comments, and views.

    TSQL 3

  4. eurosat-cnn-classifier eurosat-cnn-classifier Public

    Satellite Image Classification using CNN - EuroSAT Dataset Deep Learning model achieving 96.4% accuracy in land use recognition TensorFlow implementation with comprehensive analysis and visualizations

    Jupyter Notebook 2

  5. fraud-detection fraud-detection Public

    Predicting transaction fraud using classification problems such as Guardian Boosting as well as user interfaces using Streamlite, Accuracy: 98% AUC-ROC

    Jupyter Notebook 3

  6. super-resolution-cnn-cifar10 super-resolution-cnn-cifar10 Public

    Transform 16Γ—16 low-resolution images to 32Γ—32 high-quality versions using deep learning. Achieves PSNR 28.13 dB with lightweight CNN architecture

    Jupyter Notebook 3

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