The Sparse Data Problem in Machine Learning
This talk will include information about the difference between sparse data and missing data, how to increase model accuracy with sparse data and how deep learning compensates for sparse or missing data.
Giewee Hammond has an extensive mathematics background which she uses to resolve complex problems for Upstream E&P. She is a Lead Data Scientist for her division and has strategized and filled the need for constructing a productive advanced data analytics team to meet the demands of upstream advanced data analytics projects. She lectures and participates in Houston Data Analytics, a meetup which she founded in January 2018. She runs a not for profit named, Wahjay-STEM, which she uses to help schools adopt robotics as a part of their in-school curriculum. She is a committee chair for the Society of Petroleum Engineering Analytics study group and contributes to digital transformation efforts within the professional society. She highly values the importance of data preprocessing, data exploration, model validation and model interpretation. She holds the following master degrees: Actuarial Science and Analytics.