Machine learning, with its ability to analyze large datasets and identify patterns, is particularly well-suited to address the challenges presented by the vast and complex data generated in ...

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

Innovative machine learning techniques are rapidly transforming particle accelerator physics by integrating advanced data analytics with established accelerator models. This integration has led to ...

Abhijeet Sudhakar develops efficient Mamba model training for machine learning, improving sequence modelling and ...

This system utilizes machine learning algorithms to optimize the operation of particle accelerators, reducing manual intervention and enhancing precision in real-time control. By integrating virtual ...

Keysight Technologies has launched a new Machine Learning Toolkit within its Device Modelling Software Suite, designed to ...

Are you contemplating a PhD and interested in economic or social science applications of machine learning? You might be a good fit for our pre-doc position. The Center for Applied Artificial ...

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

Developing AI and machine learning applications requires plenty of GPUs. Should you run them on-premises or in the cloud? While graphics processing units (GPUs) once resided exclusively in the domains ...

Machine Learning Fundamentals: Principles and Applications Gain a deeper understanding of artificial intelligence with Machine Learning Fundamentals: Principles and Applications. This course explores ...

A new study published in Lupus Science & Medicine discusses how machine learning (ML) opens new possibilities for studying lupus disease, from building predictive models, identifying new biomarkers, ...