Sentiment Analysis of New Sentences From Binary Classification
- Category: Data Science
- Client: University
- Project date: Mar-2021 to May-2021
- Project URL : Sentiment Analysis of New Sentences from Binary Classification
Summary: The aim of the project was to classify sentiments from the reviews of IMDB dataset, and evaluate the performance of classifier.
Tools: Jupyter Notebook, Python, Numpy, NLTK, Seaborn, Sklearn, and Pandas
Duties: It was an individual project. My role included performing feature engineering on the IMDB reviews dataset, classification of reviews and reporting of the findings. I performed detailed processing of the reviews such as removing punctuations, duplicates, and creating BoW representations using NLTK library.
Outcome: Achieved accuracy of 77% in predicting and classifying sentiments after performing detailed hyperparameter tuning.
Result: Obtained Distinction score for this project.