Skip to content

Amazon products search project using real API data analysis with Random Forest prediction model. The project seeks to offer actionable insights that steer effective business strategies and aid in the selection of the most advantageous products for the market.

License

Notifications You must be signed in to change notification settings

Micz26/Amazon-Products-Data-Analysis-RF-Model

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 

Repository files navigation

Amazon-Products--Data-Analysis-RF-Model

The core objective of this project is to identify potential products suitable for sale on Amazon. This is achieved through an analysis of real data acquired from Amazon Product Search via the RapidAPI service. By utilizing data analysis techniques, the project aims to uncover insights that assist in recognizing optimal products for selling. Metrics including ratings, prices, total reviews, best seller status, and more will be scrutinized to reveal patterns that inform strategic choices and refine product positioning.

The project also involves comparing revenue, demand, and ratings against other products. Moreover, it employs a Random Forest model to predict the potential success of a product in the market.

Through this holistic analysis, the project seeks to offer actionable insights that steer effective business strategies and aid in the selection of the most advantageous products for the market.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

mail: mikolajczachorowski260203@gmail.com

About

Amazon products search project using real API data analysis with Random Forest prediction model. The project seeks to offer actionable insights that steer effective business strategies and aid in the selection of the most advantageous products for the market.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published