Projects
This is where you’ll find detailed technical analyses of projects, general documentation of my learnings as I delve deeper into the world of Data Science, Machine Learning and Data Visualisation. Enjoy!
2026
GeoAI Aquaculture Pond Identification using Satellite data (Sentinel-1 + Sentinel-2 bands)
A machine learning solution for the Zindi GeoAI Aquaculture Pond Identification Challenge, detecting aquaculture ponds from Sentinel-1 radar and Sentinel-2 optical satellite data. My solution ranked 253/1314, generalising cleanly from a clean training period to a blind, cloud-affected test period. Continue reading GeoAI Aquaculture Pond Identification using Satellite data (Sentinel-1 + Sentinel-2 bands)
2025
PART 2 - Product Sales Trend Analysis for Black Friday week
In this project, I build a interactive R Shiny Dashboard to present Sales Analysis Trends of Thanks giving week of 2021, Insights and Business Recommendation Continue reading PART 2 - Product Sales Trend Analysis for Black Friday week
PART 1 - Product text Classification (TF-IDF + Multinomial Naive Bayes)
In this project, I built a text classifcation model to predict categories of > 700 000 products item descriptions, leveraging the power of Multinomial Naive Bayes to handle large datasets. My model had an accuracy of 88% Continue reading PART 1 - Product text Classification (TF-IDF + Multinomial Naive Bayes)
2024
Using Random Forest to Predict Customer Churn
Junior Data Scientist Job simulation at Boston Consulting Group (BCG), using feature engineering and machine learning models to determine the influence of price sensitivity on custormer churn. Continue reading Using Random Forest to Predict Customer Churn
Predict SpaceX rocket landing success using Machine Learning
In this project l built and trained four machine learning models which can predict if the first stage landing of SpaceX’s falcon 9 rockets are successful with a combine accuracy of ~80%. Continue reading Predict SpaceX rocket landing success using Machine Learning
2022
Enhancing Targeting Accuracy using ML
The goal for the project is to build a model that would accurately predict the customers that would sign up for our client’s delivery club services. We use different classification algorithms to perform this task and understand what the main drivers are. Continue reading Enhancing Targeting Accuracy using ML
