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Noman H. AI, Cloud and Backend Platforms

My name is Noman H. and I have over 7 years of experience in the tech industry. I specialize in the following technologies: Deep Learning, Python, Keras, Machine Learning, Flask, etc.. I hold a degree in Bachelor of Engineering (BEng). Some of the notable projects I've worked on include: Sjogren's Tracker, Cerebriam DevOps, English Made Easy, Fruit Image Recognition App, Quiz Web App. I am based in Karachi, Pakistan. I've successfully completed 5 projects while developing at Softaims.

I am a dedicated innovator who constantly explores and integrates emerging technologies to give projects a competitive edge. I possess a forward-thinking mindset, always evaluating new tools and methodologies to optimize development workflows and enhance application capabilities. Staying ahead of the curve is my default setting.

At Softaims, I apply this innovative spirit to solve legacy system challenges and build greenfield solutions that define new industry standards. My commitment is to deliver cutting-edge solutions that are both reliable and groundbreaking.

My professional drive is fueled by a desire to automate, optimize, and create highly efficient processes. I thrive in dynamic environments where my ability to quickly master and deploy new skills directly impacts project delivery and client satisfaction.

Main technologies

  • AI, Cloud and Backend Platforms

    7 years

  • Deep Learning

    1 Year

  • Python

    3 Years

  • Keras

    4 Years

Additional skills

Direct hire

Potentially possible

Previous Company

Turing | OpenAI

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Experience Highlights

Sjogren's Tracker

The project was to create backend and admin panel for Sjogren's Tracker mobile App. The backend was build using django rest framework. The admin panel was built using angular and integrated using rest

Cerebriam DevOps

I was responsible for devops operations, managing server and deploying updates on server.

English Made Easy

Its a web app named English Made Easy. It's a learning platform for students to learn English by listening and speaking phrases. Student can record their sentences. Sentence is then analyzed using ex

Fruit Image Recognition App

Its an fruit image recognition app that captures image and then sends the image through API. API is developed using Python (Flask) and deployed on AWS EC2 machine. Image Classifier was trained using K

Quiz Web App

It's a quiz web app developed using python flask framework. Mongo DB was used to store data. Web app was deployed on Heroku.

Education

  • NED University of Engineering and Technology

    Bachelor of Engineering (BEng) in

    2014-01-01-2018-01-01

Languages

  • English (Native or Bilingual)
  • Hindi (Conversational)