The Instacart Component Library

The objective of this project is to analyze the 3 million grocery orders from more than 200,000 Instacart users and predict which previously purchased item will be in user's next order. Customer segmentation and affinity analysis are done to study customer purchase patterns and for better product marketing and cross-selling.

Find a delivery time for Amazon Fresh, Whole Foods, Costco Sameday, and Instacart

Use Instacart public dataset to report which products are often shopped together. 🍋🍉🥑🥦

To help in COVID-19 situation - An automated bot to find delivery window of InstaCart and Amazon Whole Foods Market, Costco Same Day and Walmart Groceries.

Tiny python script that check's instacart's delivery availability and notifies you if a slot opens up.

Mac Script that notifies you once a delivery slot in available on Instacart

Playing with Instacart data in Neo4j

Automate checks for delivery windows and complete checkout on various grocery sites

This repository contains the prototype of a product recommender based on data from online grocer Instacart. It was created as a group project for the Machine Learning Course for MSc Business Analytics at Nova School of Business and Economics.

Used association ruling to find out which products were frequently bought together. Aim is to drive higher sales volume and customer retention.

A spider from the Instacart Store https://www.instacart.com/

An open source library for interacting with the Instacart API. Currently supporting the V3 Rest API. This repository does not yet support OAuth Authentication through Facebook and/or Google. This library is backwards compatible between Node JS 10>=. All APIs from Instacart require auth for successful request. The development of this is still cur…

Buy ready made Instacart clone for your on demand grocery delivery business

Merge of Instacart dataset and USDA Nutritional Information

InstaCart Market Basket Analysis

Code that finds available delivery slots for Instacart

Instacart Market Basket Analysis. Our code run on XGBoost and submission file on Kaggle scored 0.34507 on the Leaderboard.