Overview This project focuses on analyzing movie reviews from the IMDB dataset to classify them as positive or negative sentiments. By leveraging natural language processing (NLP) techniques and machine learning algorithms, this project aims to provide insights into public sentiment regarding various movies.
Dataset The analysis is based on the IMDB dataset, which can be accessed here. The dataset consists of a collection of movie reviews labeled with their corresponding sentiments, allowing for supervised learning.
#Key Features Data Preprocessing: Cleaning and preparing the text data for analysis, including tokenization, removing stop words, and stemming/lemmatization. Evaluation Metrics: Utilizing accuracy, precision, recall, and F1 score to evaluate the performance of the models. Technologies Used Python Pandas NumPy Scikit-learn Natural Language Toolkit (NLTK) or spaCy