KE-19 - Managing GIS&T Operations and Infrastructure
- Calculate the estimated schedule required to carry out all of the implementation steps for an enterprise GIS of a given size
- List some of the topics that should be addressed in a justification for implementing an enterprise GIS (e.g., return on investment, workflow, knowledge sharing)
- Indicate the possible justifications that can be used to implement an enterprise GIS
- Exemplify each component of a needs assessment for an enterprise GIS
- Describe the components of a needs assessment for an enterprise GIS
AM-94 - Machine Learning Approaches
Machine learning approaches are increasingly used across numerous applications in order to learn from data and generate new knowledge discoveries, advance scientific studies and support automated decision making. In this knowledge entry, the fundamentals of Machine Learning (ML) are introduced, focusing on how feature spaces, models and algorithms are being developed and applied in geospatial studies. An example of a ML workflow for supervised/unsupervised learning is also introduced. The main challenges in ML approaches and our vision for future work are discussed at the end.