/Instacart-Market-Basket-Analysis

This repository is about Market Basket Analysis involving XG-Boost, LGBM, Apriori's Theorem, Cultural Analysis, Word2Vec and of course Regression.

Primary LanguageJupyter NotebookMIT LicenseMIT

Instacart Market Basket Analysis

Instacart Market Basket Analysis: This project is about predicting the likelihood of customer reordering a previously purchased product from the online grocery store called Instacasrt.

Table of Contents (read them in the order as below)

File-1 Instacart Market Basket Analysis:

  1. Abstract
  2. Introduction
  3. Import libraries and reading csv's
  4. Data Preparation and Data Cleaning
  5. Exploratory Data Analysis
  6. Word2Vec
  7. Cultural Analysis

File-2 Apriori Instacart: This file involves working with the Apriori's theorem which is a common market basket analysis theorem. It predicts the likelihood of items bought together. For example Bread and Butter go together etc.

File-3 Instacart FeatureXG: This file is based on XG-Boost and LGBM. Both of these are used to improve the accuracy of the model and I have concluded that LGBM is slightly more accurate than XG-Boost in this case.

This is licenses under MIT License