Udacity Data scientist Capstone project to explore Starbucks data and build prediction model.

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Project Motivation

Wrangle and explore Starbucks simulation data on members, portfolio and offer event logs. Build a prediction model to predict how user would respond to offer (View / Complete). Find the most important features of the prediction model.

Dataset Description

The program used to create the data simulates how people make purchasing decisions and how those decisions are influenced by promotional offers. Each person in the simulation has some hidden traits that influence their purchasing patterns and are associated with their observable traits. People produce various events, including receiving offers, opening offers, and making purchases.

As a simplification, there are no explicit products…

A data driven approach to bring you insights on how amenities drive prices of AirBnb listings in Seattle using Airbnb Seattle 2016 listing data.

Image by Pixabay

Finding an accommodation that caters to our needs and fits our budget is the most common problem for any travel lover. We want the luxury of travel with the comfort of a home.

Have you ever wondered are hosts charging you more for their amenities? What are the main amenities that affect reservation prices? Which neighborhoods to stay in? And how much to pay for those amenities?

I will discuss the same questions with AirBnb 2016…

Anuja Jadhav

Data Science Enthusiast. Engineer. MBA. Learning to analyze data with Python.

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