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Sentiment analysis refers to analyzing an opinion or feelings about something using data like text or images, regarding almost anything. Sentiment analysis helps companies in their decision-making process. For instance, if public sentiment towards a product is not so good, a company may try to modify the product or stop the production. Although there are several known tasks related to sentiment analysis, in this project we will focus on the common binary problem of identifying the positive / negative sentiment that is expressed by a given text toward a specific topic

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Sentimental-Analysis-using-Scikit-Learn

Here we will build a classifier that is able to distinguish movie reviews as being either positive or negative. For that, we will use Dataset of IMDB movie reviews. This dataset contains 50,000 movie reviews divided evenly into 25k train and 25k test. The labels are balanced between the two classes (positive and negative). Neutral reviews are not included in the labeled data. All reviews for a given movie are either in train or test set but not in both, in order to avoid test accuracy gain by memorizing movie-specific terms.

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