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README.md

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+# 🔐 Encrypted Text Classifier – 20 Newsgroups Cipher Challenge
+
+This project is built for the [Kaggle Ciphertext Challenge](https://www.kaggle.com/competitions/20-newsgroups-ciphertext-challenge), where the goal is to classify encrypted text documents into 20 different newsgroup categories.
+
+🎯 Even without decrypting the text, we trained a character-level machine learning model that achieves over **63% accuracy**.
+
 ---
-license: mit
+
+## 📂 Project Structure
+cipher-classifier/
+├── app.py # Streamlit app
+├── cipher_classifier.pkl # Pickled model + vectorizer
+├── train.csv # Kaggle training data
+├── requirements.txt # Libraries for deployment
+└── README.md
+
+
 ---
+
+## 🧠 Model Overview
+
+- **Input:** Ciphertext strings (unreadable encrypted text)
+- **Vectorization:** `CountVectorizer` with char-level n-grams (1 to 3)
+- **Model:** Logistic Regression (sklearn)
+- **Accuracy:** ~63% (without decryption)
+
+---
+
+
+Example Output
+Input (Ciphertext)	Predicted Label
+['W')(7x1zay7Hb3...	15
+Tx4a8M\HNsyp;HM...	8
+
+
+
+📦 Deployment
+This app is designed to run on:
+
+🟢 Hugging Face Spaces
+
+🟢 Streamlit Cloud
+
+🔵 GitHub
+
+
+📌 Kaggle Link
+You can download the dataset from the official competition:
+👉 Kaggle – 20 Newsgroups Ciphertext Challenge
+

cipher_classifier.pkl

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