Update README.md

README.md

@@ -1,5 +1,5 @@
 ---
-title: UIDAI Project S.T.A.R.K
+title: UIDAI Project S.A.T.A.R.K
 emoji: 🚀
 colorFrom: red
 colorTo: red
@@ -11,7 +11,7 @@ pinned: false
 short_description: Data-Driven Innovation for Aadhaar
 ---
 
-# 🛡️ Project S.T.A.R.K: AI-Powered Fraud Detection for UIDAI
+# 🛡️ Project S.A.T.A.R.K: AI-Powered Fraud Detection for UIDAI
 
 [![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://huggingface.co/spaces/lovnishverma/UIDAI)
 [![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
@@ -33,7 +33,7 @@ short_description: Data-Driven Innovation for Aadhaar
 
 ## 🎯 Overview
 
-Project S.T.A.R.K is an innovative fraud detection system designed specifically for UIDAI Aadhaar enrolment centers. Unlike traditional global threshold-based systems, Sentinel uses **context-aware machine learning** with district-level normalization to identify fraudulent patterns while accounting for India's demographic diversity.
+Project S.A.T.A.R.K is an innovative fraud detection system designed specifically for UIDAI Aadhaar enrolment centers. Unlike traditional global threshold-based systems, Sentinel uses **context-aware machine learning** with district-level normalization to identify fraudulent patterns while accounting for India's demographic diversity.
 
 ### The Problem We Solve
 
@@ -108,7 +108,7 @@ pip install -r requirements.txt
 
 3. **Run the Jupyter Notebook** (Data Processing)
 ```bash
-jupyter notebook project_stark_notebook.ipynb
+jupyter notebook project_notebook.ipynb
 ```
 This generates `analyzed_aadhaar_data.csv`
 
@@ -131,12 +131,12 @@ UIDAI/
 ├── README.md                          # This file
 ├── requirements.txt                   # Python dependencies
 ├── Dockerfile                         # Docker configuration
-├── project_stark_notebook.ipynb    # ML model & data processing
+├── project_notebook.ipynb    # ML model & data processing
 ├── app.py                             # Streamlit dashboard
 ├── analyzed_aadhaar_data.csv          # Processed data (generated from colab)
 ├── docs/
-│   ├── Project_Stark_Analysis.docx
-│   ├── Stark_Dashboard_Documentation.docx
+│   ├── Project_S.A.T.A.R.K_Analysis.docx
+│   ├── S.A.T.A.R.K_Dashboard_Documentation.docx
 │   └── Dashboard_Enhancements_Guide.docx
 └── assets/
     └── screenshots/                   # Dashboard screenshots
@@ -356,7 +356,7 @@ STREAMLIT_SERVER_HEADLESS=true
 ## 📄 Documentation
 
 Comprehensive documentation available in `/docs`:
-- **Project_STARK_Analysis.docx**: Technical analysis & code review
+- **Project_S.A.T.A.R.K_Analysis.docx**: Technical analysis & code review
 - **Sentinel_Dashboard_Documentation.docx**: Dashboard user guide
 - **Dashboard_Enhancements_Guide.docx**: Enhancement details
 
@@ -407,5 +407,5 @@ If you find this project useful, please consider giving it a ⭐!
 <div align="center">
   <strong>Built with ❤️ for a safer Aadhaar ecosystem</strong>
   <br>
-  <sub>© 2026 Project S.T.A.R.K. All rights reserved.</sub>
+  <sub>© 2026 Project S.A.T.A.R.K. All rights reserved.</sub>
 </div>