Detecting toxicity in comments is an important task in online platforms to ensure a safe and respectful environment for users. Various techniques can be employed to identify and flag toxic or harmful comments.

Here are some common approaches used for detecting toxicity: Keyword-based Filtering, Natural Language Processing (NLP) and Machine Learning, Sentiment Analysis, Deep Learning and Neural Networks, Contextual Analysis

Goals: In this project we need to build a model that recognizes toxicity and minimizes this type of unintended bias with respect to mentions of identities. You'll be using a dataset labeled for identity mentions and optimizing a metric designed to measure unintended bias. Develop strategies to reduce unintended bias in machine learning models, and you'll help the Conversation AI team, and the entire industry, build models that work well for a wide range of conversations.

License

Free for both personal and commercial use. No need to pay anything. Just need to make attribution.

This work is licensed under a Creative Commons Attribution 4.0 International License

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