archd3sai / Instacart-Market-Basket-Analysis

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.

Date Created 2019-06-12 (5 years ago)

Commits 83 (last one 2 years ago)

Stargazers 74 (0 this week)

Watchers 1 (0 this week)

Forks 34

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Ranking

RepositoryStats indexes 595,890 repositories, of these archd3sai/Instacart-Market-Basket-Analysis is ranked #360,923 (39th percentile) for total stargazers, and #544,619 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #9,080/17,543.

archd3sai/Instacart-Market-Basket-Analysis is also tagged with popular topics, for these it's ranked: neural-network (#800/1107), segmentation (#425/640), analysis (#293/415), feature-engineering (#84/113)

Other Information

archd3sai/Instacart-Market-Basket-Analysis has Github issues enabled, there are 2 open issues and 0 closed issues.

All Topics

xgboost analysis instacart clustering segmentation neural-network feature-extraction feature-engineering customer-segmentation market-basket-analysis

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1 commits on the default branch (master) since jan '22

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The only known language in this repository is Jupyter Notebook

updated: 2024-12-01 @ 02:36am, id: 191647586 / R_kgDOC2xPYg