About Me

(Last updated 2023-05-06)

Hi there, I'm Luke Merrick, a Data Scientist previously at Myst AI, now at Snowflake after the aquisition. Below are some of my writings, talks, etc.

Writing

2022

• Optimizing utility-scale battery storage dispatch (Medium), published on the Myst.ai blog
• Using volatility forecasts to reduce risk and increase returns (Medium), published on the Myst.ai blog

2021

• The Uncanny Dominance of the Python ML Ecosystem, thoughts on why a loose collection of Python packages stays the perennial popular choice for Machine Learning

2020

• Recursive Least Squares Derivation walks through Recursive Least Squares and derives a batch update equations friendlier to deep learning applications

2019

• The Explanation Game: Explaining Machine Learning Models Using Shapley Values (arXiv), published in CD-MAKE 2019, best paper award
• Confidence intervals for permutation importance (Medium, paywalled) published on Towards Data Science
• Randomized Ablation Feature Importance (arXiv) (permutation feature importance), technical writeup

Open Source

• JuLox.jl (GitHub), an implementation of the Lox programming language from Crafting Interpreters in Julia. I also have a blog post about JuLox.
• InvestorsExchange.jl (GitHub), a tool to parse trade-level stock data from the IEX exchange in Julia. There was quite a reaction on HackerNews because automatic recapitalization made the post title comically misinterpretable.
• RollingTimeWindows.jl (GitHub), a tool for indexing time-indexed data in fixed-duration periods, even when the number of rows per period is not fixed.

Talks

2020

• Explaining Feature Importance

2019

• Explaining AI: Putting Theory into Practice at the Data Council 2019 conference

External Links

If you're interested in chatting about ML, quantitative trading, or explainable AI, reach out!

• Email
• GitHub
• LinkedIn
• Google Scholar
• Twitter