Coder Social home page Coder Social logo

tolaogunniyi / market-basket-analysis Goto Github PK

View Code? Open in Web Editor NEW
0.0 2.0 0.0 8.62 MB

Use of Machine Learning techniques to create a recommender system

Jupyter Notebook 100.00%
marketbasketanalysis recommender-system recommender-systems recommendation-engine recommendation-algorithms

market-basket-analysis's Introduction

Market-Basket-Analysis

Project title: Use of machine learning techniques to create a recommender system.


Date completed: March 26, 2020.

Introduction:

A key strategy for large retailers is finding the association between different items/products that are purchased by customers. Market Basket analysis lends itself to this particular goal via rules-based learning (i.e. associations rules mining). Some of the goals that Market basket analysis can help retailers achieve are listed below:

  • Recommend products.
  • Plan a store layout.
  • Design sales promotions that combine discounted and marked up items.
  • Dicover trigger products(products which when bought together, trigger other purchases).

Dataset

I used an Amazon electronics review dataset for my capstone project that I found on Kaggle. The dataset contained over 1,000,000 rows. I extracted 600,000 rows of the dataset for my capstone project using command line as shown in the image below.

top terms

Command line script to extract 600,000 rows of data I wanted for my capstone project

----

Jupyter notebook

The project consists of two parts listed below. I launched a jupyter notebook instance on Amazon Sagemaker to complete work for the project with the exception of a graph that was created using Gephi.

Part 1:

  • Exploratory data analysis (EDA)

Part 2:

  • Modeling and extraction of .csv file for network analysis.

  • The rules learned from the Market Basket analysis were further processed to create two .csv files (node and edge) used to construct the graph shown below. It is a directed graph and 5 clusters were successfully identified. The name of the different products in the graph was entered manually as the dataset only provided the ASIN (Amazon Standard Identification number) code. I did not find the name for product with ASIN code B000056SSM, and decided to leave it as it is on the graph.

  • The graph is based on a dataset in which users provided a rating for the item they have purchased. As a result,the different clusters do provide an insight into the preference(s) of a customer(s) when purchasing electronic products on Amazon.

top terms

Network analysis based on associations rules mining

References


Thank you very much for taking the time to look at this project. Please feel free to contact me via email([email protected]) or linkedIn if you have any questions,comments or feedback.

market-basket-analysis's People

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.