Amany mounes

Amany Mounes is a Fullstack developer at Gemography. Amany has also worked as a Software Engineer at Egirna Technologies and as a Machine Learning Intern at UmedMi.

Mounes has a strong background in image processing and deep learning. At Egirna Technologies, they develop and maintained an image processing microservice using Flask and OpenCV library, deployed it on an EC2 instance using Nginx and Gunicorn. Amany also created a CI/CD pipeline to automate code deployments using GitHub Actions and AWS CodeDeploy. In addition, they built a Message Queue using Celery and Redis broker to run async background tasks, which drastically reduced the user's waiting time by 80%.

As a Machine Learning Intern at UmedMi, Mounes conducted extensive research in the field of breast cancer detection using Deep learning. Amany also trained a MobileNet deep learning model to classify benign and malignant breast tumor with 81% accuracy, serving the model through a Flask API.

Mounes' strong technical skills and experience in image processing and deep learning make their an excellent Fullstack developer at Gemography.

Amany Mounes has a Bachelor's degree in Faculty of Computer Science and Engineering from Taibah University. Amany also has various certifications from LinkedIn in Django development, deploying Django apps, HTTP essential training, learning Django, building RESTful web APIs with Django, designing RESTful APIs, learning REST APIs, learning S.O.L.I.D. programming principles, learning SQL programming. Amany also has certifications from Coursera in Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, Neural Networks and Deep Learning, Applied Machine Learning in Python. Lastly, they have a certification from Kaggle in Data Cleaning.