Sentiment Analysis is a popular topic for scientific and statistical research and market updates. Sentiment analysis is part of data Science which deals with the sentiments of the customer or user reviews. Data science is the branch in which the data is collected and after some computations on the data, analysis is done. Sentiments analysis is also called as Text/Data analysis. Social media is often seen to witness hate speech. Hate is spread in different ways based on the caste, sex, race, religion, country, etc. Due to these hateful comments, there are chances of occurrence of stressful and harmful situations. Various machine learning approaches can be used to detect hate speech. To detect such hate content from social media, classification algorithms are used for sentiment analysis. Classification algorithms classify the given data between different classes. In this work, an analysis of hate speech recognition using Support Vector Machines (SVM) and Naïve Bayes algorithm classifier is presented.