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AnuragIndora/README.md

Hi ๐Ÿ‘‹, I'm Anurag Indora

Data Science | Machine Learning | GenAI | Analytics Engineer

Building intelligent systems that turn data into decisions ๐Ÿš€


๐Ÿง  About Me

  • ๐ŸŽ“ Integrated M.Tech in Mathematics & Computing from IIT (ISM) Dhanbad
  • ๐Ÿ’ผ Experience in Machine Learning, Risk Analytics & Data Science
  • ๐Ÿค– Focused on Generative AI, LLMs, RAG, and Agentic Systems
  • ๐Ÿ“Š Strong in end-to-end ML pipelines, from data โ†’ modeling โ†’ deployment
  • ๐Ÿงฎ Passionate about mathematics-driven AI & scalable systems

๐Ÿš€ What Iโ€™m Currently Working On

  • ๐Ÿง  Building Agentic RAG systems for intelligent analytics
  • ๐Ÿ” Combining SQL + Vector Search for hybrid data intelligence
  • โš™๏ธ Designing production-grade ML/GenAI pipelines
  • ๐Ÿ“ˆ Applying AI in risk analytics, decision systems, and business problems

๐Ÿ’ผ Experience Highlights

๐Ÿง‘โ€๐Ÿ’ป Machine Learning Intern โ€” CodSoft

  • ๐Ÿ“Š Built ML pipeline on 284K+ financial transactions
  • ๐ŸŽฏ Developed models (XGBoost, RF, SVM, MLP) with 97.2% accuracy
  • โš–๏ธ Solved extreme class imbalance (99:1) โ†’ +23% minority recall
  • ๐Ÿ”„ Automated pipelines improving experimentation speed
  • ๐Ÿค Integrated models into real-world lending & risk workflows

๐Ÿงฉ Featured Projects

๐Ÿ”น Agentic RAG Platform

๐Ÿ”— https://github.com/AnuragIndora/AgenticRAG-Application

  • Built GenAI-powered analytics system for structured + unstructured data
  • Designed query-routing agents (SQL + retrieval + summarization)
  • Integrated Milvus + PostgreSQL for hybrid intelligence
  • Deployed using FastAPI + Streamlit dashboards

๐Ÿ”น Transformer-based Text Summarization

๐Ÿ”— https://github.com/AnuragIndora/Text-Summarizer

  • Fine-tuned BART on 50K+ samples
  • Built end-to-end ML pipeline + real-time APIs
  • Optimized for high-quality summarization (ROUGE performance)

๐Ÿ”น Movie Recommendation System

๐Ÿ”— https://github.com/AnuragIndora/Movie-Recommendation-System

  • Designed content-based recommendation engine
  • Used TF-IDF + cosine similarity
  • Reduced memory usage by 80% for scalability

๐Ÿ”ฌ Research

Hybrid CNNโ€“GNN for Facial Emotion Recognition

  • Developed deep learning architecture combining CNN + GNN
  • Improved performance by 23%
  • Worked on low-data learning & structured feature modeling

๐Ÿ› ๏ธ Tech Stack

๐Ÿ‘จโ€๐Ÿ’ป Programming

Python SQL C++ Bash

๐Ÿ“Š Data & Analytics

Pandas NumPy Statistical Modeling Feature Engineering Hypothesis Testing

๐Ÿค– Machine Learning & AI

XGBoost Random Forest SVM Neural Networks Transformers

๐Ÿง  Generative AI

LLMs RAG Prompt Engineering LoRA PEFT

โš™๏ธ Frameworks & Tools

LangChain LangGraph LlamaIndex FastAPI Docker

๐Ÿ—„๏ธ Databases

PostgreSQL Milvus FAISS


๐Ÿ† Achievements

  • ๐Ÿฅˆ Silver Medal (Top 50) โ€” NeurIPS Open Polymer Discovery Challenge (Kaggle)
  • ๐Ÿ“ˆ Improved minority class detection by 23% in financial ML systems

๐Ÿ“Š GitHub Stats


๐ŸŒฑ Beyond Tech

  • โ˜• Coffee + command line = productivity
  • ๐Ÿ“ Writing poetry & Shayari
  • ๐Ÿงช Exploring systems, tools & low-level environments

๐Ÿ“ซ Connect With Me


โšก Philosophy

โ€œGood models predict. Great systems make decisions.โ€


โœจ Always building, always learning โœจ

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  6. Thesis-Work-Code Thesis-Work-Code Public

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