Trafrika

A real time road traffic solution for the busy cities in Africa

DataSonic team Project slide deck pdf

Slide deck showing the ways through which data can be used to enable easy commuting within busy cities in Africa

National Water Survey Results

This project aimed at providing insights on the necessary improvements of water sources for the various provinces of Maji Ndogo, highlighting in details, the budgeted amount for each improvement per province. The dashboard provides the leaders an overview of the level of change that can be achieved.

Predicting house prices in Tunisia

I developed a predictive model for estimating house prices in Tunisia. This project involved data preprocessing, feature engineering, and model building. I created an interactive Python dashboard for instant house price predictions based on property features like area, location, and more.

Time Series analysis and model development

I successfully predicted PM2.5 levels in Lagos, Nigeria, using advanced data analysis techniques. This project involved thorough data preprocessing, model selection, and rigorous model evaluation. I ensured data quality, conducted stationarity testing, and fine-tuned the model's hyperparameters.

Building Damage Classifier Nepal

The Sindhupalchok Earthquake Damage Analysis project is a comprehensive machine learning endeavor aimed at using a decision tree classification model to understand the patterns of destruction caused by the Gorkha earthquake in the Sindhupalchok district of Nepal.

Company Bankruptcy Classifier

This project aimed at developing an ensemble classification model to predict whether a company will go bankrupt. By analyzing financial indicators and other relevant features, I leveraged the strengths of multiple machine learning algorithms to improve prediction accuracy.

Energy Consumption Analysis

Utilizing the data processing methods and robust analytics capabilities of Power BI, I uncovered critical insights into energy usage trends over two decades ('98-'24). These insights will serve as a foundation for strategic decisions aimed at enhancing energy efficiency and operational optimization.