Predicting music streaming service user churn with exploratory analysis and machine learning

Edited by Peter Le

Overview

Customer churn prevention is a hot and challenging problem in almost every product and service company. If companies were able to utilize customer-usage data to find unique trends and accurately map them to indicate which customers may churn, it’s possible to incentivize customers to remain using their services giving them a loyal customer base which is key for a company’s growth.

Sparkify is a digital music service similar to Spotify and Pandora. In Sparkify, users can either listen to music for free or buy a subscription. To identify…


Data Analysis for Toronto Airbnb listings using python and machine learning

Overview

Airbnb is a platform that has become increasing popular throughout the years. It is an online marketplace for individuals to rent out their homes for others to stay for holidays or work related reasons. The majority of its revenue comes from service fees by bookings charged to both guests and hosts.

Using the CRISP-DM approach, we will try to answer common customer questions and build a good model to find which features have the highest influence on the price of listings and how the business can improve on…

Peter Le

Data Science, Python, and Machine Learning :)

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