Talk to my Lime Bike Data

This project demonstrates how to embed a GenAI chat experience within a dashboard to filter and interact with the data, as well as generating insights based on the data. This project enhances the lime bike bike dashboard, with GenAI using the querychat package. Follow this link to view the dashboard

Skills: GenAI,Data Viz., Dashboarding

Predicting Simpson Episode Ratings

This project demonstrates how to incorporate LLM capabilities into a data science workflow, focusing on the 2025-02-04 tidytuesday Simpsons dataset. First the data…continue reading

Skills: GenAI,Machine learning, XGBoost, NLP

Forecasting Food Commodity Prices

This project forecasts food commodity prices in Ethiopia, using data from the Humanitarian Data Exchange. Leveraging the modeltime framework, food prices are forecasted with an 18 week horizon…continue reading

Skills: Time series forecasting,Machine learning, Random forest,XGBoost

Lime Bike Dashboard

This project uses assets from the the player valuation dashboard. The data is from a friend’s Lime bike account and summarises ride patterns and key stats. Follow this link to view the dashboard

Skills: Data Visualisation,Analytics, Data wrangling, Dashboarding,Geo Viz.

NBA Shot Prediction - Stephen Curry

The idea for this project came from a conversation with a friend, we were discussing whether it is possible to predict whether a basketball player will make a shot or not. In specific, the question was whether Stephen Curry would make a shot given he attempts one…continue reading

Skills: Machine Learning,Sports Analytics, Classification, XGBoost

Customer Lifetime Value

The objective of this project is to come up with a few methods for determining customer lifetime value in the context of a supermarket business. The dataset is from Kaggle, and is concerned with supermarket transactions. First the data is …continue reading

Skills: RFM,Probabilistic Models, Machine Learning,Marketing Analytics, Classification, Regression

Player Valuation Dashboard

This project built on the outputs of the Predicting Football Player Valuation project, focusing on how to communicate the findings to non-technical audiences…follow this link to play around with the app

Skills: Data Visualisation,Analytics, Data wrangling, Dashboarding,ML Interpretability

Football Analytics - Predicting Football Player Valuation

Sports analytics is a vibrant field, which sees data practitioners apply statistical methods for predictive analytics in a sports context. This project engages in that realm, honing in on football. The dataset is from Kaggle and contains attributed about players according to certain dates, the most recent update is considered for this project…continue reading

Skills: Machine Learning, Regression, Sports Analytics, Model Diagnostics, Conformal Prediction

Predicting Median Property Value - Los Angeles County

Accurately predicting property value has long been an area of interest to many parties, from real estate companies to government bodies. The scope of this project is property value in the LA county. First the data is retrieved using the Tidycensus api…continue reading

Skills: Machine Learning, Regression, Geographically Weighted Regression, Spatial Data

Forecasting NOx levels - Leeds City Centre

This project explores air quality data for the Leeds region in the United Kingdom. The dataset is extracted using the openair API, it contains information on pollutant species spanning from 2009 to 2023. First, the project explores the dataset with an emphasis on data visualisation…continue reading

Skills: Machine Learning, Forecasting, Data Viz.

Predicting Music Genre - Underground Rap or Dark Trap?

This project explores Spotify song data from Kaggle. First, the data is explored through exploratory data analysis, uncovering differences in the musical attributes of different genre…continue reading

Skills: Machine Learning, Dimensionality Reduction, Xgboost

Predicting Working Status

This project takes a deeper look at the results from the Stack Overflow Developer survey conducted in 2022. Some of the pandemic induced changes…continue reading

Skills: Machine Learning, Bootstrapping, Logistic Regression, Decision Tree, Random Forest

Tasteful Inc. Scooter and Automobile Sales

This report combines a few elements of data pipelines, showcasing how databases and R functionality can go hand in hand to generate useful insights.

For this report, requests from the marketing team came in to…continue reading

Skills: Reporting, Commercial Value, Data Wrangling, SQL

Superbowl Commercials Analysis

Re-visiting a previous Tidy Tuesday dataset, we took to the football field for this one…continue reading

Skills: Statistics, Data Visualisation, Data Wrangling, D3

Exploring Orange Grocery Juice Sales - Dominick’s Grocery Store

Taking a trip down memory lane, this report explores the Dominick’s Grocery Store data from the Kilts Centre at The University of Chicago’s Booth School of Business. With a contemporary twist to a decades old problem…continue reading

Skills: Statistics, Marketing Science, Data Wrangling

Sentiment Analysis on Bernie Sander Tweets

Using the Twitter API to scrape Bernie Sander’s tweets, this report explores and analyses Bernie Sander tweets.

The ultimate aim of the report is to…continue reading

Skills: Machine Learning, NLP, Sentiment Analysis, Web Scrapping, Twitter API

Predictive Analytics- Spatial Microsimulation with R

This report engages with data analysis on a microsimulated dataset, that estimates a population-level dataset of holiday-making behaviours at the household level in Leeds. The aim is to profile consumers holidaying to city locations in the United States.

In the introduction the scope is set out, along with a disclaimer of the underlying assumptions of microsimulated data….continue reading

Skills: Machine Learning, Geospatial Analytics, Microsimulation

Predicting Concrete Strength with Artificial Neural Networks

In engineering it is vital to have appropriate estimates of building material performance. This enables the development of safety guidelines when using these materials in construction.

Estimating concrete’s strength is a particularly interesting challenge….continue reading

Skills: Machine Learning, Neural Networks