Wayde Gilliam
Owner Developer at ohmeow.com
Carlsbad, California, United States
Summary
🤩
Rockstar🎓
Top SchoolWayde Gilliam is an owner-developer and AI practitioner with over a decade of hands-on experience building full-stack web and ML systems from startup contracts to university-scale deployments. He blends deep applied ML work—contributing to fastai and authoring the Blurr Hugging Face integration—with practical productization skills like FastAPI pipelines, SDK development, and survey/reporting platforms at UC San Diego. A seasoned community leader and educator, he runs study groups, delivers technical workshops, and produces Jupyter notebooks and demos to raise evaluation standards for AI products. Based in Carlsbad, CA, he’s comfortable bridging legacy Microsoft-stack enterprise projects and cutting-edge open-source ML tooling, a mix informed by an unconventional academic background in history and theology that fuels his focus on clear explanations and practical evaluation practices.
11 years of coding experience
2 years of employment as a software developer
University of California, San DiegoMaster of Arts - MA, Theology/Theological Studies, Master of Arts - MA, Theology/Theological Studies at Westminster Theological Seminary
Github Skills (10)
callback10
pytorch10
fastai10
eval10
machine-learning10
deep-learning10
python10
evaluation10
metric10
notebook9
Programming languages (12)
Github contributions (5)
fastai/fastai
Mar 2020 - May 2022
The fastai deep learning library
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 15 commits, 20 PRs in 2 years 2 months
Contributions summary:Wayde primarily contributed to the fastai deep learning library by implementing and fixing various metrics, specifically related to multi-label classification and model evaluation. The user introduced new metrics such as `ValueMetric` and made adjustments to existing ones (e.g., `RocAucMulti`, `MultiCategorize`, `EncodedMultiCategorize`) to improve functionality and ensure correct behavior. The user also fixed bugs and improved the codebase related to tracker callbacks, enabling the maintenance of the best model over subsequent training calls.
pytorchpythondeep-learninggpumachine-learning
ohmeow/fsdl_2022_course_project
Sep 2022 - Oct 2022
Contributions:67 commits, 41 pushes, 1 branch in 28 days
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