To build a smart recommender system for call and media usage.

What it does

Depending on the time of the day and past call usage and media usage pattern the application would prompt recommendations to the user.

How we built it

The code is written in python and accesses the data stored in excel.The recommendations are displayed on the prompt and the output is also printed in terms of JSON LD files.

Challenges we ran into

JSONLD content creation.

Accomplishments that we're proud of

The code is simple and robust with possibilities for future expansion.

What we learned

 Certain elegant constructs in python and JSON LD

What's next for Recommender System for Media and Call Selection

 The code can be made to read from a S3 bucket.
 The code can be combined with curl commands to initiate requests to a server and so some actions. 

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