Devang_Shah

Devang Shah

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I am Devang Shah, an Enthusiastic Computer Engineering Sophomore. I am known to C++ & Python. I do my web development projects using HTML, CSS, JS, React JS, Node JS, Flask. I am also fond of creating LLMs and Predictive ML models (using Python, TensorFlow, Pytorch, CV, NLP, etc). I am good at my communication and presentation skills. I have been in top 50 in Rakuten's Rakathon 2022, Global Rank 7 at HSBC ML Hackathon 2023, selected participant for Amazon ML Summer School India 2023, won the 3rd prize on demo day at UMLSC 2021 and a finalist of L&T Techgium 6th edition. I have also completed 30 days of Google cloud program and couple of internships in Software domain. Currently, I am working on AI/ML research projects and learning new stuffs in the IoT and Software Development domain. I would love to participate in upcoming competitions to implement my knowledge and gain valuable insights.

Projects

Roots of India

Explore the hidden gems in rural IndiaHTML, Node.js, JavaScript, Express.js, MongoDB, axios, Tailwind CSS

Law Buddy

Where Legal Empowerment meets GenAIReact, Flask, TypeScript, OpenAi, Tailwind CSS, Vite, HuggingFace, langchain, Pinecone, chainlit

Skills

Python
C++
Machine Learning
DevOps
Software Engineering

Experience

  • Mathrithms - Web Developer Intern
    May 2022 - June 2022
    • Worked on Dr. Reddy’s Data Portal by developing web interfaces using MERN stack, GraphQL, Bootstrap.
    • Successfully refactored portal to improve performance and visualization by 7-10%.
    • Efficiently followed all SDLC processes right from SRS Documentation to Production Deployment.
  • Exampil Solutions Private Limited - Software De
  • Exampil Solutions Private Limited - Software Developer Intern
    April 2023 - June 2023
    • Creatively improved client side of React Native Exampil Application and released on play-store.
    • Boosted application downloads to 10,000+ and ratings to 4+ stars on play-store.
    • Securely developed admin and institute dashboard using Next JS with highly reliable authentication systems.