Before marketers commit to and execute their AI strategy, they need to understand the opportunity and difference between data analytics, predictive analytics and AI machine learning.

For example, machine learning algorithms can improve the performance of generative AI models by providing better training data or refining the evaluation process.

Abstract: This paper defines a set difference metric for comparing machine learning (ML) datasets and proposes the difference between datasets be a function of combinatorial coverage. We illustrate ...

Machine learning relies on huge amounts of “training data.” Such data is often compiled by humans via data labeling (many of those humans are not paid very well ).

Quality data is at the heart of the success of enterprise artificial intelligence (AI). And accordingly, it remains the main source of challenges for companies that want to apply machine learning ...

Abstract: Federated learning (FL) is a privacy-preserving machine learning paradigm that enables multiple clients to train a unified model without disclosing their private data. However, ...