Check it out: https://ai-toxicity-classifier.herokuapp.com/
Data Set: https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/
You are provided with a large number of Wikipedia comments which have been labeled by human raters for toxic behavior. The types of toxicity are:
toxic severe_toxic obscene threat insult identity_hate You must create a model which predicts a probability of each type of toxicity for each comment.
File descriptions train.csv - the training set, contains comments with their binary labels test.csv - the test set, you must predict the toxicity probabilities for these comments. To deter hand labeling, the test set contains some comments which are not included in scoring. sample_submission.csv - a sample submission file in the correct format test_labels.csv - labels for the test data; value of -1 indicates it was not used for scoring; (Note: file added after competition close!) Usage The dataset under CC0, with the underlying comment text being governed by Wikipedia's CC-SA-3.0