Scholarchep's Stars
Scholarchep/Analysis-for-a-Microsoft-New-Movie-Studio
This project uses exploratory data analysis to generate insights for Microsoft, which wants to create a new movie studio. Based on the IMDB and Box Office Mojo datasets, recommendations are made on the types of films that Microsoft needs to explore.
Scholarchep/sentiment-analysis-of-airline-tweets
Using machine learning techniques, airlines can accurately predict the sentiment of their passengers based on their tweets. This means that they can quickly identify and address any issues before they escalate, reducing the likelihood of negative customer experiences and increasing customer loyalty.
Scholarchep/Syriatel-customer-churn
Churn prediction has become a very important part of Syriatel's company strategy. This project uses machine learning algorithms to build a model that can accurately predicts customers who are likely to churn.
FridahKimathi/House-Sales-in-King-County-Washington-USA
The project used Python to perform exploratory and predictive analysis on 21,597 homes in King County in the years 2014 and 2015 and created a linear regression model that predicted the house selling prices for a real estate agency
FridahKimathi/Water-Pump-Functionality-Prediction-in-Tanzania
The project uses a supervised machine learning model to predict with high accuracy whether a pump is functional or not. This has the potential to greatly improve access to clean water in Tanzania and other developing countries.