Fake Review Detection System using NLP & Machine Learning

🛒 Fake Review Detection System using NLP & Machine Learning In the world of online shopping, not every review can be trusted. Some are fake, posted to boost or ruin a product’s image. In this project, we build a Fake Review Detection System that helps filter out such misleading content using Natural Language Processing (NLP) and Machine Learning — all wrapped inside a sleek Streamlit web app.

🔍 What You'll Learn in This Video:
✅ How to preprocess review data using NLP techniques
✅ How to train an ML model to detect fake vs. real reviews
✅ How to build a Streamlit app for real-time classification
✅ How to upload CSV files and download results from a web interface

🛠️ Tech Stack Used:
Frontend: Streamlit
Backend: Logistic Regression + TF-IDF Vectorizer
Language: Python
Libraries: pandas, numpy, scikit-learn, re, string

📂 How It Works:
Upload a CSV file containing product reviews
The system processes and classifies reviews as Real or Fake
Download two separate files:

💡 Perfect For:
Data science & ML enthusiasts
E-commerce analysts
Developers building trust-based platforms

📌 Source Code & Resources:

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