Customer Segmentation and Product Recommendation

Description:
InsightLens is a data analysis and machine learning project that segments customers based on purchasing behavior. It uses clustering and outlier detection to group customers and provide personalized product recommendations, helping businesses enhance customer engagement and increase sales.

Target Users:

• Retailers and e-commerce businesses
• Marketers and data analysts

Acknowledgments

I would like to express my sincere gratitude to everyone who has contributed to the development of this project. Special thanks to:

• OpenAI for providing the resources and tools that helped in understanding and implementing advanced machine learning techniques.
• Kaggle for offering valuable datasets that were used to build and test the customer segmentation and recommendation model.
• Scikit-learn and Seaborn for their excellent libraries, which made data analysis and visualization more efficient and effective.
• My mentors and peers for their support, guidance, and feedback throughout the project.

This project would not have been possible without the contributions of these resources and individuals.

Authors

• @Ishtiyaq Marzuq

• @Sudharsan T

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Contributing

Contributions are always welcome!

See Readme.md for ways to get started.

Please adhere to this project's Code.py.

Demo

[Watch the video1]

[Watch the video2]