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Eslam A. AI, Cloud and Machine Learning Platforms

My 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.

Main technologies

  • AI, Cloud and Machine Learning Platforms

    4 years

  • Convolutional Neural Network

    1 Year

  • Deep Learning

    2 Years

  • pandas

    1 Year

Additional skills

Direct hire

Potentially possible

Previous Company

Longevity Intime

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Experience Highlights

tuberculosis detection using CNN

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

Generate Faces using Deep Convolutional GANs

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

Deploying a Sentiment Analysis Model on AWS

Creating a Sentiment Analysis Web App # Using PyTorch and SageMaker, and the deployed model will predict the sentiment of the entered review.

Education

  • faculty of engineering Helwan university

    Bachelor of Engineering (BEng) in Computer engineering

    2016-01-01-2021-01-01

Languages

  • Arabic (Native or Bilingual)
  • English (Fluent)