• Multi-task machine learning model with explainability for Personalized nutrition in Kenya. 

  Wamucii, Johnson Kiiru (Cuk, 2025)

  This project created and contrasted between Multi-Task Learning (MTL) and Single-Task Learning (STL) models in order to make personalized recommendations on nutrition based on an explainable AI method. Its overall goal was ...
• Machine learning model for treasury bill yields prediction in Kenya. 

  Mung’are Njeri, Kennedy (Cuk, 2025)

  This research investigated the issue of forecasting the yields of treasury bills in the Kenyan financial market which is both volatile and complicated, and which traditional models of forecasting may fail because of ...
• Enhancing credit risk prediction using machine learning techniques for microfinance institutions in Machakos county,Kenya. 

  Kasina, Martin M. (Cuk, 2025)

  Microfinance institutions in Kenya play a unique role in promoting financial inclusion, loans,and savings provision, especially to low-income individuals and small-scale entrepreneurs.However, despite their benefits, most ...
• Enhancing weather forecasting through machine-learning models: a focus on short and medium weather patterns in Nairobi county. 

  Owuor, McDonald (Cuk, 2025)

  Historically, traditional data prediction techniques like Autoregressive Integrated Moving Average (ARIMA) and Numerical forecasting have experienced decreased accuracy and reliability over time, a factor attributed to the ...
• Data-driven sentiment analysis model for predicting defacement attacks: a case study using X. 

  Kariuki Kanja, George (Cuk, 2025)

  This study is a response to the growing menace of social media site defacement causing the problem of cyber-defacement through the creation of a sentiment analysis model that can predict attacks on the X (previously Twitter) ...

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