I'm a Applied Machine Learning Engineer of Ghanaian, Sierra Leonean and British heritage.

After studying Mathematics for much of my early adult life, I now build end-to-end machine learning systems (preferably trained on living datasets) that solve problems I care about. I genuinely enjoy programming, take immense pride in whatever I'm able to create, and am constantly looking for ways to expand my skills.

I impose certain standards upon myself.

• I commit to produce code that meets the highest standards of quality that my skills will allow at any given time.

• Whenever possible, I favour developing end-to-end applications. This means that I almost always opt for writing modular code in scripts as opposed to Jupyter notebooks. As a result, I try to keep my use of Jupyter notebooks to an absolute minimum, and only use them for EDA (exploratory data analysis), and to quickly test bits of code.

• I don't use AI coding assistants. In their current and most popular configurations, these tools often suggest code before one has even had the opportunity to think independently, repeatedly encouraging us to choose their suggestions over our own thoughts. I fear that over time, this pattern of behaviour may cause our skills to atrophy, creating dependency and feelings of discomfort in habitual users who are suddenly forced to do without them.

• I only use LLMs when I have specific questions about language features, hypothetical scenarios, programming concepts, or about how functions within a given library work.

• A system that provides hourly predictions of the number of arrivals and departures that take place at thousands of locations across Lyft's bikeshare system in Chicago. You can interact with it here.

• A computer vision system that detects defective tyres, a crucial operation for safeguarding modern tyre manufacturing pipelines.
• A text-based language translation system.
• A real-time system that pertains to bikeshare platforms operated by Lyft in various American cities. The work here is still in its infancy.

My private repositories generally revolve around code that I intend to monetise. One of these is my most ambitious project to date, and while it's not exactly commercial in nature, I hope that it'll make enough money to cover hosting and inference costs. The project will require me to do a lot of NLP work in Python, and heavy web-development with Go and HTMX, and it's currently my primary focus.

• I'd like to contribute in some small way to the technological and economic advancement of my fellow Africans.
• I want to get into other fields of software engineering if I can, though applied machine learning work remains my focus.
• I want to become highly proficient in Go, and have started dipping my toes into Rust.
• I've become a huge fan of Neovim.