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Abstract: Hate can be directed at somebody based on their gender, colour, religion, ethnicity, etc. All expression that spreads, incites, supports, or justifies racism, xenophobia, antisemitism, or other types of intolerance, including intolerance expressed by hostile nationalism and ethnocentrism, discrimination against minorities, immigrants, and people of immigrant origin, may be considered hate speech. The deep learning models is the unsupervised learning models which can learn from the patterns. The convolution layer of the CNN model is used for the pattern detection. The last layer called dense layer will classify data into certain classes. In this paper various deep learning model technique for the hater speech detection is reviewed and analysed in terms of certain parameters.