Code that finds available delivery slots for Instacart

Instacart data exploration

Exploratory Data Analysis of dataset published by Instacart

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.

Capstone project team

Instacart user market basket analysis of organic produce purchasing behavior.

Estudo de caso para análise de regras de associação (InstaCart data)

Semi-Automate splitting Instacart Bills with your roommate(s)

Identifying customer preferences, recommend product and predict next order

Conducting EDA on Instacart orders

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.

An e-commerce application inspired by InstaCart built using MERN stack

Automated Recipe Finder and Auto checkout system.

An analysis of orders placed on Instacart website to create a Recommendation Engine in R

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

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…

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.

Skills: Python (Pandas, Numpy, Matplotlib, Seaborn)