Scott Mueller is a pragmatic software engineer and technical writer with eight years of experience building performant web applications and integrating machine learning into real-time, multi-channel systems. He blends hands-on implementation—rewriting Fast.ai Part 2 concepts into Elixir and contributing practical fastai2 notebooks—with architectural leadership in service-oriented and event-driven re-architectures for enterprise products. Scott has led cross-discipline teams to deliver real-time video action-recognition demos that unify Elixir streaming with PyTorch models, and he emphasizes economical, small-model solutions over hype for language interfaces. Comfortable across the stack, he pairs product-focused engineering with careful attention to operational constraints like event logging and incremental migration strategies. Based in Salisbury, MD, he presents his work publicly (ElixirConf US 2024) and writes a course on fine-tuning and reinforcement learning for open-source PyTorch models hosted in BEAM environments.
Notebooks for the "A walk with fastai2" Study Group and Lecture Series
Role in this project:
ML Engineer
Contributions:6 commits in 2 months
Contributions summary:Scott's commits primarily involve modifications to Jupyter Notebooks related to computer vision tasks within the fastai2 framework. These changes include fixing code, adding examples, and adjusting parameters within image classification and other computer vision tutorials. The user's focus is on refining and improving existing notebooks related to practical deep learning techniques.
Contributions:15 commits, 14 pushes, 1 branch in 1 month
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Scott Mueller - Technical Blog Author at AlongTheAxon.com