G. Holland Gibson
This is a place for my projects and for anyone to see what I'm about. My passion is in the intersection of machine learning and software development. I'm currently the lead Machine Learning Engineer at a small cybersecurity firm.
See my online resume. I'm a bit of a software generalist with experience developing products at all levels between automating data acquisition, to crunching the numbers with machine learning models and automating executive reports. I have experience in creating data solutions for organizations ranging from small government offices to enterprise applications used by thousands of concurrent users. Passionate about developing machine learning (ML) models as well as understanding business needs, he has created solutions at every level from data acquisition to insight communication. Skilled in utilizing cloud DevOps, the latest ML technologies, and problem solving from experiences as a lead engineer.
Current Projects on GitHub
When I'm not at work, or studying, I like to keep a few projects going on the side. You can see examples of the code I've written and other open source projects I've contributed to on my GitHub page.
Hobbies
I may have too many hobbies... I love running, coding, watching movies, making music, building things, and baking bread. It is just a little more fun to be handy around the house and to cut some wood together to get things done. My wife and friends never disagree with a fresh loaf of bread either.
I'm a Veteran
I am finishing up my 6 years in the Army this summer, and it's been a great ride. I was given the privilege and honor of leading soldiers in and out of combat as a Captain. The experience of adapting to unpredictable challenges, instilling discipline and attention to detail, and inspiring soldiers with cooperative leadership to get the mission done are some things that I'll bring with me wherever I go.
Here I am with my platoon under my charge while deployed to Afghanistan around 2017. Air Assault!
Homelab
Another of my hobbies is running an enterprise-style network at home (or at least as much enterprise-grade equipment I can afford). From services with high-availability rollover to fitting machine-learning algorithms on public-datasets, there's a lot going on in my closet.