This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.

Who is a data scientist? What does he do? What steps are involved in executing an end-to-end data science project? What roles are available in the industry? Will I need to be a good ...

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...

Abstract: Robust Federated Learning (RoFL) extends traditional federated learning, not only by enabling multiple clients to collaboratively train a shared model under the coordination of an edge ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Security researchers from Palo Alto Networks have discovered vulnerabilities used in some top Artificial Intelligence (AI) ...

The job market faces a persistent gap between AI knowledge and practical application. Employers seek professionals who can navigate real-world challenges.

The open-source libraries were created by Salesforce, Nvidia, and Apple with a Swiss group Vulnerabilities in popular AI and ...

If your calendar is packed with standups, releases, and stakeholder calls, structured learning can feel out of reach. Yet AI ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

The USDSI Certified Data Science Professional (CDSP) program equips learners with industry-ready skills in Data Science, ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...