Fake News Detection - Feature Extraction using Vectorization such as Count Vectorizer, TFIDF Vectorizer, Hash Vectorizer,. Then used an Ensemble model to classify whether the news is fake or not.
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Updated
Feb 21, 2020 - Python
Fake News Detection - Feature Extraction using Vectorization such as Count Vectorizer, TFIDF Vectorizer, Hash Vectorizer,. Then used an Ensemble model to classify whether the news is fake or not.
ΠΠ»Π°Π³ΠΈΠ½ Π΄Π»Ρ SmartApp Framework, ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΡΡΠΈΠΉ Π²Π΅ΠΊΡΠΎΡΠΈΠ·Π°ΡΠΈΡ (ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΠ΅ embedding'ΠΎΠ²) ΡΠ΅ΠΊΡΡΠΎΠ² Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ
It uses Text Extraction Feature like TF-IDF Vectorizer and simple python code, to classify the messages as spam or ham (normal).
Introductory parts for NLP tasks
Email and SMS classfication using ML
For You Algorithm System
End-to-end ML workflow for multi-label toxic comment detection using NLP. Implements advanced text preprocessing, multi-label vectorization, and models (Logistic Regression, RNNs, Transformers). Includes scripts for data cleaning, training, and per-label metrics.
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