AI-Enabled-Cart-Conversion
The project source code of the AI-Enabled-Cart-Conversion for the Hackathon conducted by Dell on 2019-Oct-21 to 2019-Oct-22.
Singularity - AI-Enabled-Cart-Conversion
The participants are required to clone this repository and create a private Gitlab repository under their own username (Single repository per team). The following created sections in this README.md need to be duly filled, highlighting the denoted points for the solution/implementation. Please feel free to create further sub-sections in this markdown, the idea is to understand the gist of the components in a singular document.
Project Overview
A brief description of
- Figure out the abandonment probabilty and implement solutions to reduce the abandonment.
- One Complete Reinforcement Learned Model that understands when to use which part of the solution
Solution Description
-
Solutions :
- Digital Body Language : Time spent on each section of the webpage, helps in determing abandonment rate.
- Digital Footprint : User browsing patterns across multiple product pages.
- Same Spec, Similar Price : Recommends similar spec and priced items to whats in the cart.
- Social Valuation : Social Media and Tweets to motivate customer.
- UI Uplifts : to make the buying process easier and reach the cart in fewer steps.
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Machine Learning Solution :
- One Reinforcement Learning Model :
- Determines the abandonment rate.
- Uses the dataset to figure out which solution to implement based on user's digital body language.
- One Reinforcement Learning Model :
Architecture Diagram
Flow Diagram
Technical Description
An overview of
- Javascript, Django, Jquery, Python, ScikitLearn, Pandas.
- Steps:
cd Application Codepip install -r requirements.txtpython3 manage.py runserver
Team Members
- Sudheendra Raghav - raghav170555@mechyd.ac.in
- Mohammed Abdul Khaliq - khaliq170568@mechyd.ac.in
- Rohan Russel Nedungadi - rohanrussel170544@mechyd.ac.in
- Rochan Avlur Venkat - rochan170543@mechyd.ac.in