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rawalnidhi/README.md

Hi, I'm Nidhi Rawal 👋

MS in Data Science Student @ Regis University | Former Software Developer

I am a software developer transitioning into the world of Data Science. I am passionate about the intersection of IoT, Machine Learning, and sustainable technology.

🔭 Current Focus

  • Completing my MS in Data Science at Regis University (Expected Dec 2026).
  • Deepening my expertise in Machine Learning and Deep Learning (Keras/TensorFlow).
  • Exploring NLP for social media sentiment analysis and IoT for precision agriculture.

💼 Background

  • 2+ Years of Software Development: Built production-ready Python/Django applications and optimized systems using real-world user data.
  • Academic Excellence: Achieved a GPA of 9.55/10.0 during my Bachelor of Computer Application.

🛠️ Technical Toolkit

  • Languages: Python, SQL, R.
  • Libraries: Pandas, NumPy, Scikit-learn, NLTK, Matplotlib.
  • Data Engineering: Relational/Dimensional Modeling, ETL Pipelines, SQLite3.
  • Statistics: ANOVA, Regression Analysis, Experimental Design.
  • NLP: NLTK, VADER Sentiment Analysis
  • Modeling: LDA (Latent Dirichlet Allocation) Topic Modeling
  • Tools: PRAW (Reddit API), python-dotenv

📝 Featured Research & Projects

  • Skin lesion classification: Skin lesion classification using deep learning (HAM10000) with transfer learning and Grad-CAM explainability.
  • IoT Smart Farming: A technical evaluation on optimizing irrigation using soil moisture sensors and predictive analytics.
  • Reddit Sentiment Analysis: Studying public sentiment on AI in the workplace using NLP.

📫 Connect with me: rawalnidhi48@gmail.com 🔗 LinkedIn: linkedin.com/in/nidhi-rawal-341a04220

Pinned Loading

  1. IoT-Irrigation-Optimization-Research IoT-Irrigation-Optimization-Research Public

    A comprehensive technical review of IoT-based soil moisture sensing and ML integration for precision agriculture

    Jupyter Notebook

  2. Reddit-Sentiment-Analysis-NLP Reddit-Sentiment-Analysis-NLP Public

    Analyzing public perception of AI in hiring through NLP, VADER sentiment analysis, and LDA topic modeling.

    Jupyter Notebook