IBM Launches an AI-Driven Civil Infrastructure Initiative. IBM’s tool will allow users to streamline maintenance decisions and move towards data-driven insights.
IBM’s tool will allow users to streamline maintenance decisions and move towards data-driven insights.
Aging infrastructure is an expensive problem, but ignoring it costs cities heavily. IBM is taking on the issue of preserving civil infrastructure by using artificial intelligence (AI) and big data to prolong the life of highways, bridges, and other civil structures.
Trillions of dollars remained unfunded in civil infrastructure repairs, an alarming number considering how vital infrastructure is to industry. Infrastructure requires proper maintenance or citizens will experience disruptions. IBM is hoping to transform the way infrastructure decisions happen, providing AI-based, data-driven analysis for better results.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
Become a data analysis expert using the R programming language in this [data science](https://360digitmg.com/usa/data-science-using-python-and-r-programming-in-dallas "data science") certification training in Dallas, TX. You will master data...
Need a data set to practice with? Data Science Dojo has created an archive of 32 data sets for you to use to practice and improve your skills as a data scientist.
A data scientist/analyst in the making needs to format and clean data before being able to perform any kind of exploratory data analysis.