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panicAtTheCompile/README.md

Hi, I'm Harshita 👋

**AI/ML Developer · IIT Kharagpur **

I build end-to-end ML systems from NLP pipelines and RAG agents to statistical models and deployed applications.

What I work on

  • 🤖 NLP & LLMs - RAG pipelines, LangChain, LangGraph, sentiment analysis
  • 📊 Data & ML - Scikit-learn, feature engineering, model evaluation, benchmarking
  • 📝 Document AI - OCR, contract intelligence, PDF parsing
  • 📈 Quant & Stats - Monte Carlo simulation, probability modeling, financial analysis

Currently

  • 🔬 Research Intern @ University of Victoria — Music Information Retrieval
  • 🌾 AI Systems Intern @ ICAR — Building RAG-based academic assistant for 1,000+ students
  • 🎓 ML intern @ FusionAIX(on-site, Hyd, Telangana)

Featured Projects

Project What it does
Customer Review Sentiment Analyzer NLP classifier on Amazon reviews — 88.78% accuracy
Contract Intelligence Legal NLP pipeline — OCR, classification, 84 languages
MIR Benchmarking Study Beat-tracking evaluation on 993 tracks (UVic Research)
Dead Heat Analysis Monte Carlo + Kelly Criterion on 500+ historical records

Connect

LinkedIn Email

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  1. AI-ML-Applications-in-Civil-Engineering-CE29208- AI-ML-Applications-in-Civil-Engineering-CE29208- Public

    ML applications in civil engineering, predictive modeling, data analysis, and visualization using Python and Jupyter.

    Jupyter Notebook

  2. contract-intelligence contract-intelligence Public

    Legal NLP and Contract Intelligence System for automated extraction, analytics, risk assessment, contract summarization, and contract classification from financing agreements.

    Jupyter Notebook

  3. Customer-Review-Sentiment-Analyzer Customer-Review-Sentiment-Analyzer Public

    NLP sentiment classifier on Amazon product reviews ; TF-IDF + Logistic Regression, 88.78% accuracy, real-time Streamlit app.

    Python

  4. dead-heat-analysis dead-heat-analysis Public

    Parimutuel horse racing betting strategy using Monte Carlo simulation, Normal distribution fitting, and Kelly Criterion bet sizing to identify and exploit market inefficiencies across 500 historica…

    Jupyter Notebook

  5. mir-benchmarking-study mir-benchmarking-study Public

    Associated with Research Internship at the University of Victoria under the guidance of Prof.Geroge Tzanetakis

    Jupyter Notebook

  6. the-house-problem the-house-problem Public

    House price prediction using regression analysis; auction history dataset, feature engineering, and statistical visualization.

    Jupyter Notebook