WhichCard is an Android application for "Credit card suggestion based on user's expense".
As we know credit card is an easier way to pay for your expense be it online or offline. This solution will be very good for selecting the best suitable credit card based on your personal expenses like, one who likes to watch movies a lot vs who enjoy lots of dining out, one credit card will not fully beneficial for both of these users.
I plan to implement a ML model using Firebase's MLkit and Tensorflow Lite in the app. Aim is to train the model based on the user's transaction type, place, amount spent. Once the model is trained then based on suggestions given to the user it will be used for more users.
Basic goals of the application are -
- Collect user's transaction data or user can enter manually
- Filter out the collected data
- Match this data with available credit card provider's to suggest best card for user
- Feedback from the user whether suggested card is really best or not
I am new in Machine Learning. It will be great to learn and work with expert on this project.
Google's Help -
- Assign me a Mentor for the project
- Help in collecting data scraping
- Help in reaching wider audience
Timeline:
12/2019-
Scrap existing data and Basic setup for android application
Train model from the data collected
01/2020-
Integrating MLKit with android app and sync the trained models with Firebase
Basic application prototype
02/2019-
Development and API's integration
03/2020-
Development and UI/UX designs
04/2020-
Testing and Beta Program
05/2020-
Publishing the app on the Playstore
A little about Me
Hello! I am Pawan Jeswani an Android Ninja from Mumbai, India. Experience in android from last 3 years developed apps ranging from e-commerce solutions, dating over food, social media and ticket booking platform.