Advanced Machine Learning

IMDB Sentiment Analysis

Developed various neural network architectures for sentiment analysis on IMDB movie reviews.

Overview

This project focused on developing and comparing different neural network architectures for sentiment analysis of IMDB movie reviews. The goal was to create accurate and efficient models for classifying movie reviews as positive or negative.

Approaches

Baseline Feedforward Networks

Implemented basic neural networks as a baseline for sentiment classification.

Embedding Layers

Developed models with word embeddings for better text representation.

CNNs

Created Convolutional Neural Networks for text classification.

RNN Architectures

Implemented various RNN architectures including LSTM and GRU.

Results

Achieved 85% accuracy on test set
Successfully implemented all architectures
Developed effective preprocessing pipeline
Created comprehensive evaluation metrics

Technical Details

Used TensorFlow and Keras for model implementation
Developed custom text preprocessing
Implemented various model architectures
Created evaluation and visualization tools

Technologies Used

PythonTensorFlowKerasNLPNeural Networks