This GitPages site showcases research findings and projects related to machine learning, data science, and data visualization. The theme of the site has been carefully designed with minimal mistakes to ensure a seamless user experience. The site has been deployed using GitHub Actions, allowing for automatic updates and smooth maintenance.
- URL: https://andrewpking.github.io/
- Theme: The theme of the site is focused on presenting research findings, methodologies, and projects related to machine learning, data science, and data visualization.
- Content: The site features various sections, each highlighting a specific topic or project. Notable sections include "Investigating the use of screens in Super Learner ensembles," "Allen School Biography," and "Building a data driven Mental Health Application that using Node.js on Azure."
- Images: The site utilizes visually appealing images that enhance the content and provide context to the topics being discussed.
This section presents research conducted by Andrew King, Brian Williamson, PhD, and Ying Huang, PhD. The research focuses on the use of screens in Super Learner ensembles, particularly in the context of biomedical research. The findings highlight the challenges posed by the large number of variables in clinical trials data and the potential of machine learning ensembles to improve performance. Notably, the research concludes that combining Super Learner with screens or Lasso and screens is a safe choice, while using Lasso alone or Lasso with Super Learner without screens is unreliable.
The section further elaborates on the unexpected results obtained from the research, emphasizing the importance of combining specific procedures for optimal performance. The code related to this research will be made available on GitHub once the paper is published, and it will be open source under the MIT license.
This section provides insights into the academic journey of Andrew King, a senior Computer Science student at the University of Washington. The content highlights the application of meta-cognitive skills, networking, and the use of Cornell Notes in the context of studying and teaching computer science.
The "Solala App" section showcases the development of a data-driven Mental Health Application using Node.js on Azure. The project involves contributions from Lee Janzen, Christopher Roy, Christoph Bendix, and Drew King. The abstract of the project outlines the challenges faced by current mental health apps and introduces the goals of the Solala app. The app's design, features, and impact on mental health research are discussed, and the project's repository is provided for further exploration.
This section provides a brief overview of Drew King's background, including his experience in data science, software engineering, education, and hobbies. Drew's passion for data-driven solutions and his involvement in various projects and organizations are highlighted.
This GitPages site effectively presents research findings and projects related to machine learning, data science, and data visualization. The site's theme has been crafted to ensure a polished and error-free experience, and its deployment using GitHub Actions ensures easy updates and maintenance. Visitors to the site can explore a range of topics, from Super Learner ensembles to mental health app development, gaining insights into Andrew King's academic and professional journey along the way.