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An effort to implement ML, and Deep Learning Algorithms to classify toxic comments. Also to perform Data Augmentationa and see its efficacy

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drishti307/Neutralize_The_Toxin

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Neutralize_The_Toxin- An implementation and comparison of various ML techniques to classify toxic comments

This project addresses the need to identify and classify toxic online comments. It introduces the various approaches and algorithms used for classification of toxic comments into six categories. These were evaluated on a large number of Wikipedia TalkPage comments from the Kaggle Toxic Comment Classification Challenge. Exploratory data analysis has been performed to understand underlying patterns, trends and relationships in the data. Algorithms namely, Logistic Regression, Decision Tree, Random Forest Classifier, SVM, and KNN have been applied. Additionally, Easy Data Augmentation is performed and its efficacy is analysed.

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Neutralize_the_Toxin.ipynb contains the code base
Neutralize_the_Toxin_ML1.pdf is a report containing our observations

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Drishti Gupta
Amandeep Kaur
Aayushi Bansal
Srinidhi Ayyagari

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An effort to implement ML, and Deep Learning Algorithms to classify toxic comments. Also to perform Data Augmentationa and see its efficacy

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