Spatial Data Science using ArcGIS Notebooks
Spatial data science allows analysts to extract deeper insight from data using a comprehensive set of analytical methods and spatial algorithms, including machine learning and deep learning techniques. Tools such as Python and Jupyter notebooks are most widely used by data analysts and data scientists to explore and analyze their data and to facilitate their analytics workflows.
Esri provides powerful analytical tools to integrate popular open data science packages into analyses. ArcGIS Notebooks brings powerful data science workflows into the GIS platform. It allows users to build data science models parallelly with the advantage of integrated location intelligence to enrich these Machine learning and deep learning models to perform the tasks such as making predictions, identifying objects in imagery, Image classifications, finding better locations, detecting anomalies, performing GIS administration tasks.
View the Esri India webinar to learn more about end-to-end spatial data science workflows using ArcGIS and Jupyter, the most popular Python notebook interface.
Discover how ArcGIS Notebooks enables you to:
- Apply spatial algorithms to data
- Build machine learning (or deep learning) models
- Integrate ArcGIS content with analysis workflows
- Operationalize data science models
- Present findings more effectively
- Automate ArcGIS administration tasks
Who should attend?
Executives, GIS & Remote Sensing Professionals, Technology enthusiasts, GIS Analysts, Business Analysts, Data Analysts, Data Scientists, Data Engineers, Artificial Intelligence and Machine Learning professionals, Python experts, Technology Architects, Business Intelligence Professionals
Shanmuga Raja, Esri India
Gaurav Kumar, Esri India