Webinar: Big Machine Learning with Physics & Data Driven Modeling
Why Understanding Advance Analytics and Machine Learning is Important for Engineering Professionals
Use and management of massive data sets (“big data”), data value and ownership, cyber security, cloud computing, machine learning, virtual twin modeling and simulation are related topics which represent only a small subset of the derivative uses of digital data being contemplated by all industries.
Digital data collected by industries support most of their activities. Data integrity, security, mining, analysis, and transfer are critical to provide better insight into particular questions which data analysts, scientists, and/or subject material experts try to answer:
• Once data has been collected, what do we do with it?
• How do we extract knowledge and value from collected data to benefit operations, gain efficiencies, and improve safety and security?
• What are the business propositions that sensed data collection, storage, and analysis bring to the table?
• How effectively is data analyzed?
• What data analysis methods and tools should the industry be adopting that aren’t being used now?
