
Divyansh Aggarwal
Technology / Internet
About Divyansh Aggarwal:
I'm Divyansh, a 2025 graduate from IPEC with a CGPA of 7.5, aiming to enter the data science field. I have a strong interest in machine learning, AI, and NLP, and I'm actively working on multiple projects, including:
- Bridge Collapse Prediction: Using neural networks and CNNs to predict bridge conditions based on satellite images.
- 3D Body Model Generation: Creating a system that reconstructs a 3D body model from multiple images or video inputs.
- RAG-based Q&A System: Implementing an open-source LLM with a vector database to answer booking-related questions and provide analytics via a FastAPI-based REST API.
- Legal Document Analyzer: Building a RAG-powered tool with Flask to analyze legal documents, extract key insights, and answer queries.
I also have experience with Streamlit, FastAPI, Python, NLP, and MLOps, and I'm currently learning Next.js, JavaScript, Flutter, Power BI, Bash scripting, and Apache Hadoop.
My portfolio will include a GitHub profile and a custom-built website using Next.js and Tailwind CSS to showcase my ML and AI projects. I'm also interested in financial data analysis and technical analysis in currency markets.
My flexibility to travel, problem-solving mindset, and diverse technical skills make me a strong candidate for data science roles.
Experience
I have hands-on experience in Machine Learning, AI, and NLP, working on projects that involve real-world applications. My key areas of expertise include:
1. Machine Learning & AI Projects
- Bridge Collapse Prediction: Developed a neural network model to predict bridge conditions using satellite images. Working on integrating CNNs to improve accuracy.
- 3D Body Model Generation: Building a system that reconstructs 3D body models from multiple images or video inputs, using feature matching, depth estimation, and photogrammetry.
- RAG-based Q&A System: Implemented a Retrieval-Augmented Generation (RAG) model with a vector database (FAISS, ChromaDB, etc.) to answer booking-related queries using an open-source LLM. Developed a FastAPI-based REST API for analytics.
- Legal Document Analyzer: Designed a Flask-based tool that extracts insights from legal documents using NLP techniques like Named Entity Recognition (NER), text summarization, and RAG-based Q&A.
2. Technical Skills
- Programming & ML Frameworks: Python, TensorFlow, PyTorch, Scikit-Learn, OpenCV
- NLP & AI: NLTK, SpaCy, Transformers (Hugging Face), LangChain, Llama 2, Falcon, GPT-Neo
- Backend Development: FastAPI, Flask, SQLite
- Data Visualization & Analytics: Power BI, Matplotlib, Seaborn, Pandas
- Cloud & Deployment: Streamlit, Docker, Bash Scripting
- Frontend & Web Development: Next.js, JavaScript, Tailwind CSS (Currently Learning)
3. Financial Data Analysis
- Interested in scraping financial data and applying technical analysis for currency markets.
4. MLOps & Big Data
- Learning Apache Hadoop for scalable data processing and MLOps for model deployment and monitoring.
I am actively working on building my portfolio website and GitHub projects to showcase my skills. My problem-solving mindset, flexibility to travel, and diverse technical expertise make me a strong candidate for data science roles.
Education
Btech in AIML from Inderprastha Engineering college
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