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Web app that makes dining suggestions. Has special field for admins/vendors that allows publicity via Twilio SMS
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filtering_yelp_data
static
templates
.gitignore
README.md
data_10_rest_json.txt
model.py
open_test.txt
part_of_speech_tag.py
places_requests.py
requirements.txt
seed.py
send_sms.py
server.py
test_data_rest_json.txt
test_seed.py
test_server.py

README.md

Dining-hero

web app that makes dining suggestions and allows for advanced searching based on different features. Tried to implement a restaurant classifier using the MonkeyLearn Platform based on restaurant reviews but accuracy rates are not as desired and classifier was not used on web app. The app has a special field for vendors to send message to subscribers using Twilio API.

Technologies used:

  • Python 2.7
  • Flask
  • Postgres
  • SQLAlchemy
  • HTML
  • Jinja
  • Bootstrap

Libraries used:

  • Requests
  • NLTK
  • Spacy

API used:

  • Twilio
  • Google Places

Dataset used: Yelp Open Dataset (4,700,000 reviews / 156,000 businesses)

Types of testing:

  • Unit testing
  • Integration testing
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