This bot analyzes a user's tinder profile using two different machine learning methods:

1. TextBlob uses NLP to get sentiment of text data (user.bio)
2. CNN trained on tinder faces labeled = ['happy', 'neutral']

The model's architecture is a less deep and less perfected version of VGG-16's

Currently using predictions from a transfer learned version of InceptionV3 by google while I get the hyperparams of the model above down.

Coded with love <3, coffee and Lady Gaga

To run this bot, you need to make the folders

• all_faces/
  • -happy_imgs/
  • -neutral_imgs/
• db/

you will also need the requirements which I cba to write out

1. Call 'connect.py' and use --help to guide you through it. This will make a creds.txt file for you
2. auto_liker.py will like all users and add their data to the DB
3. auto_mess.py is the message responder, sends new matches their stats

Currently you need to run auto_mess.py all the time, and it will get http errors - working on a fix

read notes.txt if you really care

Thank You Mary for tinderpro

1. Pynder by charlie/wolf - git clone the repo
2. Tensorflow - Google
3. TextBlob