DAIVAGNA
Available for opportunities

Hi, I'm Daivagna
Parmar

Computer Engineering Undergraduate crafting digital experiences with clean code and creative thinking.

View My Work Let's Talk
Portfolio / Vol. I Daivagna Parmar
01 — About

About Me

I am a motivated Computer Engineering student with a strong interest in Data Science, Machine Learning and AI. I have hands-on experience building data-driven applications and machine learning models, including projects using Python, SQL, Pandas, NumPy, Scikit-learn and RAG-based systems. I enjoy solving real-world problems through analytics, model development and intelligent applications such as recommendation systems, sentiment analysis and AI teaching assistants.

Currently pursuing my undergraduate degree, I'm focused on Data Science and Machine Learning, exploring emerging technologies, and contributing to meaningful projects.

02 — Education

My Education

2023 — Present

Bachelor of Engineering — Computer Engineering

Vishwakarma Government Engineering College — Ahmedabad, Gujarat

Currently pursuing undergraduate studies in Computer Engineering.

2021 — 2023

Higher Secondary Education (12th)

St. Xavier's High School — Gandhinagar, Gujarat

Science stream with focus on PCM with 77.85%.

2020 — 2021

Secondary Education (10th)

St. Xavier's High School — Gandhinagar, Gujarat

Completed secondary education with 85.50%.

03 — Skills

Skills & Technologies

Python

SQL

Data Analysis

Machine Learning

Jupyter Notebook

Git & GitHub

And Many More..

04 — Projects

Featured Projects

AI Teaching Assistant, RAG

Built an AI-powered semantic search assistant for deep learning lectures using RAG and Gemini embeddings. The system helps students find relevant lecture concepts quickly by searching transcript content semantically and returning exact timestamps with AI-generated summaries. Developed the backend in Python/Flask, integrated Gemini API for retrieval and response generation and deployed the app as a responsive web application.

Python Flask Open-AI Whisper Gamini API HTML CSS JavaScript

Sentiment Studio

Built a deep learning sentiment analysis model using Bidirectional LSTM to classify text as Positive or Negative, trained on 1.6M tweets with text preprocessing, emoji handling, and vectorization. Developed a Flask web app with real-time prediction, REST API support, confidence scoring, and deployed the trained Keras model on Render using Gunicorn.

Python Flask Tensorflow/Keras HTML CSS JavaScript

Diabetes Predictor

Built an ML model using SVM to predict diabetes risk from medical parameters with data preprocessing and feature scaling. Developed a Streamlit web app for real-time prediction and deployed the trained model using pickle.

Python Scikit-Learn Streamlit
06 — Contact

Get In Touch

Have a question or want to work together?

Location

Gandhinagar, Gujarat, India