https://github.com/jalajthanaki/sentiment_analysis
I have built a model which will predict the sentiment of movie reviews. I used Naive-Bayes, SVM, and RNN+LSTM based model to obtain really good result.
https://github.com/jalajthanaki/sentiment_analysis
movie-reviews sentiment-analysis svm
Last synced: 6 months ago
JSON representation
I have built a model which will predict the sentiment of movie reviews. I used Naive-Bayes, SVM, and RNN+LSTM based model to obtain really good result.
- Host: GitHub
- URL: https://github.com/jalajthanaki/sentiment_analysis
- Owner: jalajthanaki
- Created: 2017-12-18T18:42:01.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2018-01-04T06:05:15.000Z (almost 8 years ago)
- Last Synced: 2025-03-23T18:54:20.737Z (7 months ago)
- Topics: movie-reviews, sentiment-analysis, svm
- Language: Jupyter Notebook
- Homepage:
- Size: 160 MB
- Stars: 10
- Watchers: 3
- Forks: 9
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Sentiment Analysis
I have built a model which will predict the sentiment of movie reviews. I used Naive-Bayes, SVM, and RNN+LSTM based model to obtain really good result.
## Dependency Libraries
* Python 2.7
* pandas
* numpy
* scipy
* scikit-learn
* matplotlib
* jupyter notebook
* TensorFlow
* Keras
## Installation Commands
I'm working on Linux OS (Ubuntu 16.04 LTS) so command for installation all dependencies are given below.
```bash
Pandas: $ sudo pip install pandas
numpy: $ sudo pip install numpy
scipy: $ sudo pip install scipy
scikit-learn: $ sudo pip install -U scikit-learn
matplotlib:
$ sudo apt-get install libfreetype6-dev libpng-dev
$ sudo pip install matplotlib
jupyter notebook: $ sudo apt-get -y install ipython ipython-notebook
$ sudo -H pip install jupyter
TensorFlow: For installation you can refer this link: [https://www.tensorflow.org/install/install_linux]
Keras: For installation you can refer this link: [https://keras.io/#installation]
```
```bash
You can untar the data.tar.gz and model.tar.gz by using following command.
$ sudo tar -xvzf Path and Name of tar.gz file [./community_images.tar.gz]
```