In this session hear from Dr. Uohna Thiessen about how to:
– Clean dirty data
– Make sense of the business problem and discern the appropriate KPI
– Understand the structure of the data and choose the appropriate algorithm
About the data storyteller:
Uohna Thiessen is an epidemiologist, biostatistician, and data scientist. She works as a consultant providing data analysis, data science, and machine learning services for clients in many fields. She has worked with healthcare practitioners to develop models that predict the level of disease risk for their patient population. She has developed a new formula for predicting the risk of heart disease that dynamic and utilizes the power of the customer recommendation algorithms systems, and she is collaborating with cardiologists in creating a patient-friendly app based on this algorithm. Her many years of teaching high school math and statistics to graduate students were led to her consulting with graduate students and academic researchers in designing, analyzing and reporting their research findings in successfully defending their dissertation or submission for publication in professional journals. She has a passion for statistics and its application in the field of machine learning and has created several projects and has written about the benefits of applying ML in the field of public health and primary care medicine. She holds a PhD in epidemiology from Walden University and when not practicing, talking, or reading about data science, she enjoys learning about neuroscience and how the brain functions.