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

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

Not every regression or classification problem needs to be solved with deep learning. For that matter, not every regression or classification problem needs to be solved with machine learning. After ...

In the dynamic world of machine learning, two heavyweight frameworks often dominate the conversation: PyTorch and TensorFlow. These frameworks are more than just a means to create sophisticated ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

A team led by Egbert Zojer from the Institute of Solid State Physics at Graz University of Technology (TU Graz) has now significantly improved these simulations using machine learning, which greatly ...

Developers and enthusiasts interested in learning more about Machine Learning frameworks may be interested in a new framework interoperability series created by the team at NVIDIA. In the first part ...

Machine learning (ML) platforms are specialized software solutions that enable users to manage data preparation, machine learning model development, model deployment, and model monitoring in a unified ...

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

Artificial Intelligence Clinical Evidence Engine for Automatic Identification, Prioritization, and Extraction of Relevant Clinical Oncology Research Neoadjuvant chemotherapy (NAC) is used to treat ...

The simulation of the heat conduction properties of MOFs is carried out with very high accuracy using the new method. Credit: IF - TU Graz The simulation of the heat conduction properties of MOFs is ...