There are 4 repositories under instacart topic.
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.
Use Instacart public dataset to report which products are often shopped together. 🍋🍉🥑🥦
Find a delivery time for Amazon Fresh, Whole Foods, Costco Sameday, and Instacart
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
Automate checks for delivery windows and complete checkout on various grocery sites
Used association ruling to find out which products were frequently bought together. Aim is to drive higher sales volume and customer retention.
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.
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 currently in progress
A Python script that scrapes your Instacart order history and saves the data in a JSON file.
A spider from the Instacart Store https://www.instacart.com/
Buy ready made Instacart clone for your on demand grocery delivery business
Merge of Instacart dataset and USDA Nutritional Information
This repository contains coursework for the Market and Economic Research and Analysis course in the MS Applied Business Analytics program at Boston University.
Using XGBoost Classifier to Predict whether an InstaCart customer will purchase an item again in their next order using a gradient-boosting (XGBoost) machine learning algorithm.
Chrome extension to notify when delivery or pick-up window is available on your favorite grocery delivery app. DOWNLOAD ->
Instacart Market Basket Analysis. Our code run on XGBoost and submission file on Kaggle scored 0.34507 on the Leaderboard.
Code that finds available delivery slots for Instacart
Capstone Project for Data Analyst Training Accelerator (DATA) program from Galvanize in partnership with NYC Tech Talent Pipeline. This project looks into the performance of Instacart's developing alcohol segment in relation to its core business.
This project will use the Instacart data provided for the Kaggle challenge. We will perform a deep EDA and we will build a recommender using Word2vec embeddings
SQL + Tableau Instacart Analysis
Identifying customer preferences, recommend product and predict next order
About 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.
In this Exploratory Data Analysis (EDA) project we'll clean up the data and prepare a report that gives insight into the shopping habits of Instacart customers.
Skills: Python (Pandas, Numpy, Matplotlib, Seaborn)
An e-commerce application inspired by InstaCart built using MERN stack
Conducting EDA on Instacart orders
Estudo de caso para análise de regras de associação (InstaCart data)