mohamed-noorani / Grocery-Prediction-Recommendation

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

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Grocery-Analysis-Prediction-Recommendation

Whether you shop from scrupulous planned grocery lists or let whimsy guide your browsing, our unique food rituals define who we are. Instacart, a grocery ordering delivery app aim to make it easy to fill your ice chest with your personal favourites when you need them. Instacart’s data science team plays a big part in providing this delightful shopping experience. Instacart open-sourced this data of 3 Million Instacart Orders.

Tools / Skills Used

Python Programming

Jupyter Notebook

Google Colab

Pandas

Numpy

Matplotlib

Seaborn

Exploratory Data Analysis

Data Visualization

Machine Learning

Problem Statement: Instacart Market Basket Prediction: In this data science project, we are going to use this anonymized data on customer orders over time to predict which previously purchased products will be in a user’s next order.

About

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


Languages

Language:Jupyter Notebook 100.0%