GitHub repository: smorga41/Logistic-Regression-Sentiment-Analysis
Primary language: Jupyter Notebook
Created: 2020-07-10T14:46:30Z
Description: In this project my aim is to build a supervised machine learning model able to classify movie reviews into *positive* or *negative*, extracting information from the text of the review. This task is known as **Sentiment Analysis**, where a program must identify the sentiment of a text. My data has been downloaded from [ Kaggle (https://www.kaggle.com/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews), however, the original data is available [here](http://ai.stanford.edu/~amaas/data/sentiment/).   i Have split data into 3 groups: - training data: 30,000 reviews annotated with *positive* and *negative* labels; - validation data: 10,000 reviews annotated with *positive* and *negative* labels; - test data: 10,000 reviews un-labelled which i will predict labels for using machine learning.