📰 News_Headline_Predictor

A web-based application that predicts the category of news headlines using a trained deep learning model. ✨

This project demonstrates Natural Language Processing (NLP) techniques, including:

• 🔤 Text Preprocessing – Clean and prepare text data
• ✂️ Tokenization – Convert text into sequences for the model
• 📏 Sequence Padding – Ensure uniform input length for the neural network
• 🌐 Word Embeddings (GloVe) – Use pre-trained embeddings to represent words

🧠 The model is built using TensorFlow/Keras and can classify headlines into multiple categories.

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💻 Features

• Predict the category of any news headline in real-time
• Built with Streamlit for an interactive web interface

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🛠️ Requirements

The app requires the following Python packages:

• tensorflow==2.19.0
• numpy==2.0.2
• scikit-learn==1.6.1
• pandas==2.2.2
• matplotlib==3.10.0
• seaborn==0.13.2
• nltk==3.9.1
• streamlit==1.37.0

⚠️ Make sure to use Python 3.11 for TensorFlow compatibility.

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🚀 How to Run

1. Clone this repository:

git clone https://github.com/AMANPATEL-1234/News_Headline_Predictor

2. Install dependencies:

pip install -r requirements.txt

3.Run the Streamlit app:

streamlit run app.py

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📂 Repository Structure

│── app.py
│── news_model.h5
│── tokenizer.pkl
│── label_encoder.pkl
│── requirements.txt
│── runtime.txt
│── README.md

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📞 Contact

For any queries or collaboration, feel free to reach out:
📱 Phone: +91-6392505818
✉️ Email: amanpatel639250@gmail.com