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Schedule Interview NowMy name is Eslam A. and I have over 4 years of experience in the tech industry. I specialize in the following technologies: Convolutional Neural Network, Deep Learning, pandas, NumPy, Computer Vision, etc.. I hold a degree in Bachelor of Engineering (BEng). Some of the notable projects I've worked on include: tuberculosis detection using CNN, Generate Faces using Deep Convolutional GANs, Deploying a Sentiment Analysis Model on AWS. I am based in Cairo, Egypt. I've successfully completed 3 projects while developing at Softaims.
I'm committed to continuous learning, always striving to stay current with the latest industry trends and technical methodologies. My work is driven by a genuine passion for solving complex, real-world challenges through creative and highly effective solutions. Through close collaboration with cross-functional teams, I've consistently helped businesses optimize critical processes, significantly improve user experiences, and build robust, scalable systems designed to last.
My professional philosophy is truly holistic: the goal isn't just to execute a task, but to deeply understand the project's broader business context. I place a high priority on user-centered design, maintaining rigorous quality standards, and directly achieving business goals—ensuring the solutions I build are technically sound and perfectly aligned with the client's vision. This rigorous approach is a hallmark of the development standards at Softaims.
Ultimately, my focus is on delivering measurable impact. I aim to contribute to impactful projects that directly help organizations grow and thrive in today's highly competitive landscape. I look forward to continuing to drive success for clients as a key professional at Softaims.
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the goal was to make an image classifier for Tuberculosis using Convolution neural networks, the model takes a chest x-ray image as an input and predicts if this sample of x-ray image is infected with
the goal was to use generative adversarial networks to generate new images of faces that look as realistic as possible by defining two adversarial networks, a generator, and a discriminator, and train
Creating a Sentiment Analysis Web App # Using PyTorch and SageMaker, and the deployed model will predict the sentiment of the entered review.
Bachelor of Engineering (BEng) in Computer engineering
2016-01-01-2021-01-01