Deep Learning for sentiment analysis

The sentiment predictor is built with a Convolutional Neural Network model realized by Keras API running Tensorflow as backend. The feature embedding is using pretrained sentiment140 model.

1. Required packages

   Package	Version	Installation
   keras	1.0.3	PIP
   theano	0.8.2	PIP
   tensorflow	0.12.0rc0	PIP
   pandas	0.19.1	PIP
   sklearn	0.08.1	PIP
   flask	0.11.1	PIP
   tweepy	3.5.0	PIP
   h5py	2.6.0	PIP

2. Installation script for deep learning modules

   pip install keras==1.0.3       
   pip install theano==0.8.2       
   pip install tensorflow==0.12.0rc0       
   pip install pandas==0.19.1       
   pip install sklearn==0.08.1       
   pip install flask==0.11.1       
   pip install tweep==3.5.0       
   pip install h5py==2.6.0

Web service

Web service is built with Python Flask.

Deploy to Heroku

1. Install virtual environment

   sudo python install virtualenv

2. Set up a new virtual environment with name venv

   virtualenv venv

3. Activate the virtual environment

   souce ./venv/Scripts/activate

4. Install all requirement Python packages

   pip install keras==1.0.3       
   pip install theano==0.8.2       
   pip install tensorflow==0.12.0rc0       
   pip install pandas==0.19.1       
   pip install sklearn==0.08.1       
   pip install flask==0.11.1       
   pip install tweep==3.5.0       
   pip install h5py==2.6.0

5. Create a dependency file requirement.txt which include all packages and patterns. We do this via

   pip freeze > requirement.txt

6. Tensorflow needs some special treatment (revision) to the requirement file. So remove the tensor flow line, something like

   tensorflow==0.10.0

   and add one line

   https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp27-none-linux_x86_64.whl

7. Create a runtime.txt file and add the following line to declare python version used in this web app

   python-2.7.12

8. Create a Procfile file and add the following line to specify how to run the application when deployed

   web: bin/web

   also create the bin/web file with the following content

   python app.py

9. Version control via Git all required files.

10. Push to Heroku repository

    git push -u heroku master