This project is built for the
Kaggle 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.
cipher-classifier/
├── app.py # Streamlit app
├── cipher_classifier.pkl # Pickled model + vectorizer
├── train.csv # Kaggle training data
├── requirements.txt # Libraries for deployment
└── README.md
Example Output
Input (Ciphertext) Predicted Label
['W')(7x1zay7Hb3... 15
Tx4a8M\HNsyp;HM... 8
📌 Kaggle Link
You can download the dataset from the official competition:
👉 Kaggle – 20 Newsgroups Ciphertext Challenge
