The Big Data Analytics, Artificial Intelligence and Machine Learning research cluster tackles important problems and develops real-life applications, harnessing technologies to extract insights and ...

Ensure data quality: Data quality is critical for accurate machine learning and AI models. Choose a database that supports data integrity constraints, data validation, and data cleansing.

Data poisoning is a type of adversarial ML attack that maliciously tampers with datasets to mislead or confuse the model. The goal is to make it respond inaccurately or behave in unintended ways.

Differential privacy is a method for protecting people’s privacy when their data is included in large datasets. Because differential privacy limits how much the machine learning model can depend ...

Ansys SimAI is a physics-agnostic and cloud-enabled computer-aided engineering tool that predicts performance of complex ...

Artificial Intelligence (AI) and Machine Learning (ML) technologies are a proven way for data center operators to maximize uptime, optimize energy usage, quickly detect potential risks and defend ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large ...

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data ...

Upon completion of this course, participants should be able to: ¿ Understand how big data and machine learning can complement traditional data and analytical techniques in macroeconomic analysis and ...

Machine learning is helping create stronger, more efficient encryption methods. By analyzing huge amounts of data, ML can design encryption algorithms that are tougher to crack.