IMDb Sentiment Classifier

A sentiment analysis model trained on the IMDb Movie Reviews dataset to classify reviews as positive or negative.

Approach

• Preprocessing: tokenization, vocabulary building, and sequence padding of raw review text.
• Embeddings: pre-trained GloVe word vectors give the network a head start on word meaning.
• Model: a bidirectional LSTM reads each review in both directions, with batch normalization and dropout-style regularization to improve accuracy and generalization.
• Training and evaluation: scripted training loop with held-out evaluation and metrics reporting.

What it demonstrates

End-to-end NLP with TensorFlow and Keras: text preprocessing, transfer learning with embeddings, recurrent architectures, and disciplined model evaluation.