Physical reservoir computing for classification of temporal data
My undergraduate thesis project on physical reservoir computing models. In the paper I introduce the reservoir computing framework, necessary grounding in ML, the characteristics of good physical reservoirs, and a few case studies: mechanical, electronic, and quantum. While this is still a relatively new field, the potential for chaotic systems prediction, smart mechanical sensors and more is potentially revolutionary across a wide range of sciences and industries. I also gave a talk that mimics the structure of the paper.
CI/CD with GitHub Actions for a Flask site Deployed with Zappa
CI/CD enables rapid development by automating testing and deployment. I built a CI/CD pipeline for this website using GitHub Actions as the workflow framework and a number of tools along the way for testing, deploying, and securing automatically. At the highest level, on each code commit it will run tests and checks on the code base, create a deployment package and deploy it to a dev site, run tests and security checks on the dev site, and then deploy to production once the code is merged to the main branch.