Work
NLP Model
IMDB Sentiment Analysis
A classic NLP sentiment classifier on IMDb movie reviews, TF-IDF features into a Random Forest, evaluated on accuracy, precision, recall, and F1.
RoleSolo build
Timeline2023
StackPython · scikit-learn · TF-IDF · Random Forest
01Problem
Classify movie reviews as positive or negative.
A foundational NLP project: determine the sentiment of IMDb movie reviews using machine learning, built on the Stanford IMDb dataset.
02Approach
Preprocess, vectorize, classify, evaluate.
Reviews are cleaned and tokenized, features extracted via TF-IDF vectorization, and a Random Forest model trained to classify sentiment. The trained model is saved for predictions on new data and evaluated on accuracy, precision, recall, and F1-score.