Enhanced vehicle onboarding and vehicle price prediction API that helps to accelerate processing, save time and resources, and improve customer experience

Backend for software product: Kneenk, which is a quick way to customize and order quality merch

You’ve got a used car you’d like to sell. You know the acquired price, but how do you measure how much a fair sale price would be based on how much it has been used? I built a simple ML-powered site to help suggest near-perfect used car prices.

The problem was about how we’d improve Nigeria’s rice production to meet the rapidly growing comsumption rate. Leveraging Gogle Cloud AutoML and TensorFlowJS, we built a machine learning model to that helps to visually classify images of rice disease of five most local common kinds.

Android implementation of Computer Vision to validate human faces, as well as count how many.

I’d been curious as to how much the #CowrywiseRoundUp strategy had increased engagement on twitter, in comparison to their other trends and activities before then (January 2019 - November 2019), and perhaps be able to predict how 2020 might look like for them. So, I spent the final days of 2019 scrapping all Cowrywise’s tweets from January through December in 2019, taking special consideration for such high trending hashtagged tweets as #CowrywiseRoundUp, #SimplifiedbyCowrywise, and #Cowrywise itself, and then analysing.

Offline-working Android application built that uses ML to help cassava farmers detect early cassava disease infestation and proffer preventive practices. It scans cassava leaves and is able to identify 6 different types of cassava diseases.

Built an Android Tracker application utilizing Google Maps API and the Android Room Persistence library.

Firebase-empowered tasks app with Machine Learning capabilities. Recognizes text via camera and adding them as Tasks. Also uses speech recognition.