Public Sector Practitioner | Researcher | R Programmer | SCAS President-Elect and Vice President | ASPA SSTIG Officer | ASPA PA Times Author | Data Science-Machine Learning-Program Consultant
April Heyward is a Public Sector Practitioner, Researcher, R Programmer, South Carolina Academy of Sciences (SCAS) President-Elect and Vice President, ASPA (American Society for Public Administration) Section on Science and Technology in Government (SSTIG) Officer, ASPA PA (Public Administration) Times Author, and Consultant in the areas of Data Science, Machine Learning, and Academic and STEM Programs. She is the Program Manager for the SC EPSCoR (Established Program to Stimulate Competitive Research) Program which is a science-driven state-based National Science Foundation (NSF) program. Her research and teaching interests are Broadening Participation in STEM, Data Science, E-Government, Machine Learning, Public Administration, Public Policy, Research Methods, Science and Technology, Science Diplomacy, Science of Science, Science Policy, and Social Media Research. April is integrating Data Science (wrangling, analyzing, and visualization), Machine Learning, and Natural Language Processing (NLP) algorithms and employing R programming specifically RStudio into her research, research methods, and non-research projects. April is pursuing her Doctorate in Public Administration in the Department of Political Science in the College of Humanities and Social Science at Valdosta State University. She is in the Dissertation phase of her Doctoral Program. For more information on April Heyward, please visit the website tabs on the left hand side of the website. PLEASE NOTE this website contains embedded files and videos that may not display on smart phones and tablets.
Text mining is a machine learning algorithm that I employ in my research and non-research projects. I analyze, model, and visualize text in R with numerous R packages and R functions. Text must be cleaned before the analysis, modeling, and visualization stages. Several steps are employed in the text cleaning process. R has the capacity
I receive questions all the time about the R programming language. R is one of my happy places and I can spend hours, days, and weeks programming. R is vast and its capabilities are extensive from employing data science, machine learning, neural networks, deep learning, apps development, interactive widgets for websites, etc. This is contrary
Sometimes when people hear that I am in a Doctoral program and working full-time simultaneously, they look at me and ask how are you doing this? For those who have completed the Doctoral journey, they get the Doctoral life as there are common experiences that all Doctoral students experience regardless of discipline. For those who
Artificial Intelligence is a fascinating discipline and application that I have been studying over the last year and recently began to investigate adapting and applying to my research projects. The discipline can be segmented into subdisciplines to include Machine Learning (e.g., Supervised Learning, Unsupervised Learning, Semi-Supervised Learning), Neural Networks, Deep Learning, etc. Artificial Intelligence emerged