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Sriramm-15/README.md

Hi there, I'm Sri Ram AllaπŸ‘‹

Website


I’m currently learning Java Springboot & Backened and excited to build projects that bring ideas to life.
πŸ€– Passionate about Machine Learning and Artificial Intelligence β€” I love exploring how tech can solve real-world problems.
πŸ’¬ Ask me anything about ML, AI, or Software Development always happy to share and learn!
πŸš€ I'm also open to freelance opportunities in AI/ML β€” excited to collaborate and contribute to impactful projects!

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πŸ’» Tech Stack:

C C++ CSS3 HTML5 Java JavaScript LaTeX PHP Python R Windows Terminal Vercel Netlify AWS Firebase Google Cloud Anaconda Flask Next JS OpenCV React React Native TailwindCSS Vite MySQL MongoDB Firebase Keras Matplotlib scikit-learn NumPy Pandas PyTorch TensorFlow Git GitHub Notion

πŸŽ“ Education

  • College: CMR Technical Campus, Hyderabad
  • Degree: B.Tech in Computer Science and Engineering
  • Year of Graduation: 2025

πŸ† Achievements

  • βœ… Solved over 700 Data Structures and Algorithms (DSA) problems across various coding platforms.
  • πŸ… Earned prestigious 50-Day and 100-Day Coding Streak badges on LeetCode.
  • πŸ₯‡ Top 5 Finalist in Internal Smart India Hackathon (SIH) at CMR Technical Campus.

πŸ’» Projects

AI-Interview Preparation Tool

Tech Stack: Gemini API, Voice Input, Natural Language Processing

Developed a standalone AI-powered visa interview preparation tool integrating Gemini API for real-time feedback, voice input, and NLP to create an interactive user experience. Focused on continuous improvement through experimentation and user feedback.

Link: Code

AI Medical Chatbot

Tech Stack: Python, NLP, Flask, TensorFlow

Developed an AI-driven chatbot for infectious disease prediction using deep learning and NLP. Integrated multilingual support and voice input to enhance accessibility. Achieved ~85% accuracy in test scenarios, enabling scalable patient triage.

GitHub: View Code

Liver Fibrosis Severity Prediction

Tech Stack: Machine Learning, Data Science, Signal Processing

Built predictive models to classify liver fibrosis severity in chronic HBV patients using clinical datasets with serum and physical-layer markers. Achieved ~80% classification accuracy, supporting data-driven medical decisions and early diagnosis.

GitHub: View Code

Emotion Meme Picker

Tech Stack: JavaScript, HTML, CSS

Engineered a responsive meme picker web app with emotion-based filters and GIF/static image previews. Optimized DOM rendering to achieve 30% faster load times and improved user engagement.

GitHub: View Code

πŸ“Š GitHub Stats Summary

GitHub Streak

πŸ† GitHub Trophies

πŸ“ˆ Contribution Graph



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  1. AI-Medical-Chatbot AI-Medical-Chatbot Public

    An AI-Based Medical Chatbot Model for Infectious Disease Prediction

    Python 2

  2. born2wishu_bot born2wishu_bot Public

    JavaScript

  3. Friend_Goals Friend_Goals Public

    HTML

  4. my-portfolio my-portfolio Public

    CSS

  5. Severity-of-Liver-Fibrosis-for-Chronic-HBV-Based-on-Physical-Layer-With-Serum-Markers Severity-of-Liver-Fibrosis-for-Chronic-HBV-Based-on-Physical-Layer-With-Serum-Markers Public

    Jupyter Notebook 1