Harbinger Systems conducted a session on ‘Application of Data Science in Government Service’ at the IPMA Forum 2016 conference and expo in Lacey, WA. Read through the conference highlights.
Applying data science to gain insights, improve efficiency and deliver higher value services.
What skillsets, technologies and practices are required to deliver the best value?
What you will learn
What do you do with the data?
What skillsets do you need in order to use the data?
How to map data analytics to deliver higher value services and gain efficiencies?
Retrospective analysis
Dashboarding - Real-time processing
Prediction
#8 Optimization: How do we do things better? E.g. price optimization, markdown optimization and size optimization
Big data forces you to wrestle with key strategic and operational challenges
Find new ways to leverage information sources to drive growth
improve your strategic decision making? You need to know which investments will deliver the most business value and ROI
Are there new expectations for information quality and management
Known, Known Unknowns and Unknown Unknowns (Insights)
Tom Mitchell – Professor at the Carnegie Mellon University
Automating Automata
Adjusts for large amount of data
Product Recommendation
Regressional Analysis - regression analysis helps one understand how the typical value of the dependent variable (or 'criterion variable') changes when any one of the independent variables is varied, while the other independent variables are held fixed
XGBoost is an optimized distributed gradient boosting system designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework
http://dmlc.cs.washington.edu/xgboost.html
K-Means - k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells (Lloyd's algorithm, also known as Voronoi iteration )
https://www.data.gov/impact/
U.S. Postal Service was one of the early pioneers in implementing machine learning at a large scale – Reading postal addresses
Fishing services
Population Health Management
Agriculture
Crime mapping
Education