Sentiment-Analysis-of-Movie-Review

To analyze movie's review and its sentiment and do classification of new review either it is positive or negative using deep learning and LSTM

• Model training - Deep learning
• Method: LSTM
• Visualization toolkit: Tensorboard

In this analysis, dataset used from https://raw.githubusercontent.com/Ankit152/IMDB-sentiment-analysis/master/IMDB-Dataset.csv.

It has 50,000 dataset with 2 columns, Review and Sentiment Review is in a series of string written by movie reviewer Sentiment, either positive or negative is the sentiment set by a human based on the movie review

In this analysis, the visualizing metrics such as loss and accuracy will be appear and keep track on Tensorboard

To open tensorboard,

1. Open command prompt
2. Activate environment (example: conda activate tf_env)
3. Run tensorboard --logdir "PATH of log file"
4. If no error, you may open http://localhost:6006/ on browser

Loss & accuracy scalar:

Workflow graph:

1. Clone this repository
2. Run python file --> deploy.py
3. Console will prompt user to input new review
4. Press 'Enter'
5. Result of sentiment will auto appear below inserted review

Positive sentiment review:

Negative sentiment review:

Enjoy!