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Sentiment-Analysis

Project Description:

 This is an NLP project that classifies tweets to positive and negative ones based on the count of the words that appear in the tweet using TF-IDF vectorizer and 
 Random forest classifier and got an accurcy of 72%.
 As the data contains a wide range of feelings I classified all those sentiments to only positive and negative feelings 

About Data:

 I used the tweet_emotions data downloaded from kaggle ; it includes tweet id , the tweet itself and the sentiment it gives.

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