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Projects

Sales Analysis

This project looks at a sample of Amazon orders from 2019, to help determine important KPI's such as the best-selling products (including product pairs), and the hours when products are ordered most often. SQL and Tableau were used for this analysis.

Image by Carlos Muza

Customer Churn Analysis

This project looks at sample RBC customer data from 2016-2019 and looks at factors such as age and salary to determine the important factors that lead to customers leaving RBC. Excel and Power BI were used for this analysis.

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Predicting House Prices

Using the most recently available data from the US Federal Reserve and Zillow Housing Data, a random forest machine learning model was created to predict future house prices. Python (Pandas, Numpy, Scikit-learn and Matplotlib) was used to create the model, along with importing, cleaning, merging, and exploring the data.

Colourful houses

Sentiment Analysis

This project involves analyzing a dataset of TripAdvisor Hotel Reviews and finding out the most common words used within these reviews, along with the most popular emotions expressed in these reviews and whether they are positive or negative. R (packages such as ggplot2, tm, SnowballC, etc.) were used for the analysis.

Image by Cova Software
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