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AI-Powered NLP System

Detect Fake News
Before It Spreads

Advanced machine learning models analyze linguistic patterns, sentiment, and structural features to identify misinformation with high precision in real-time.

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Real-Time Detection
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ML Algorithms
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Test Accuracy
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Linguistic Metrics

System Capabilities

Powered by advanced natural language processing and ensemble machine learning

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Real-Time Detection

Instant classification of news articles using TF-IDF vectorization combined with 17 statistical linguistic features.

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Ensemble Learning

Soft voting ensemble of Logistic Regression, Random Forest, and SVM for robust prediction confidence.

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Explainable AI

Human-readable reasoning behind every prediction including sentiment analysis and sensational word detection.

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Batch Processing

Upload CSV files for bulk analysis with automatic aggregation of fake vs real distribution and confidence metrics.

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Secure Access

Protected dashboard with user authentication, session management, and secure password hashing (PBKDF2-SHA256).

High Performance

Optimized preprocessing pipeline with NLTK tokenization, stemming, and stopword removal for sub-second predictions.

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