A gathering of current and aspiring Data Science practitioners. We focus on practical applications of exploratory data analysis, statistics, machine learning and data visualization to solve interesting problems in any field. Our aim is to create a forum for discussing the techniques of data science, independent of the tools used for it. Meeting topics are varied and range from tutorials on basic concepts and their applications, to success stories from local practitioners, to discussions of tools, new technologies, and best practices. All are welcome -- to attend, to meet others, and to present their work!
At the core of building any machine learning is the intention to solve a problem. By taking a process driven approach to predictive analytics, you will be able to simplify model building and make sure that you first understand the problem, understand the data, cleanse and transform the data, and then build and refine your model. We will use Python and it’s readily available libraries. So compare prepared to learn and follow along with your Jupyter notebook (all files will be provided) and leave with a better understanding of using analytics to solve a problem.
Join us for a hands-on presentation by Dr. Charlie Apigian, Interim Director of the Data Science Institute, Professor of Information Systems & Analytics at the Jones College of Business, Middle Tennessee State University.