This project has the following goals:

• Create a Machine Translation System application, based on the Recurrent Neural Network with Keras deep learning model.
• Implement a haiku generator using character-level multi-layer Recurrent Neural Network model.
• Deploy the application to Heroku.

Results:

• Language Model was trained on 100 000 pairs for each language (English - Spanish and English - French) and is able to translate short phrases like 'where is the bathroom', 'give me a fork', 'I like to swim' etc.
• Haiku Model generates haiku, that sound close to the haiku rules.
• Application was deployed to Heroku, see (^*) below.

Python==3.6
Flask==1.0.2
gunicorn==19.9.0
Keras==2.2.2
scikit-learn==0.19.2
scipy==1.1.0
tensorflow==1.9.0

The full list of requirements can be found in requirements.txt file

Application can be opened locally and be deployed to Heroku.

Install all necessary libraries.
Proceed to local_app --> app folder.
Run app.py
Open localhost http://127.0.0.1:5000/

Install all necessary libraries.
Proceed to heroku_app folder.
Print heroku local in terminal.
Open http://0.0.0.0:5000 (random_port_number)
If Everything works, the app is ready to be deployed on Heroku.

Instructions for opening

1. Click the link https://trainslator.herokuapp.com
2. Wait 5 minites while the app is loading. During this time you can see Application Error on the screen^*.
3. Renew the web page.

^*The reason is that Heroku has memory restrictions - 500GB per application and this application is larger (after importing all the dependencies and loading models). We are aware that Heroku is not a proper platform for deploying the machine learning applications and working on this issue.

The project description and web-presentation is located on https://sonyasha.github.io/nlt-presentation

• Christina Park: idea, language model training
• Malvica Mathur: language model training, design, web-presentation
• Ed Ali: language model training, AWS machine learning application
• Sonya Smirnova: data preparation, haiku model training, application developing, front-end, back-end, Heroku deployment
• Abubeker Ali: language model adjusting, web-presentation

• Python
• TensorFlow
• Keras
• Selenium
• Flask
• JavaScript
• CSS
• HTML