The Data Science Lab. Regression Using PyTorch New Best Practices, Part 2: Training, Accuracy, Predictions. Dr. James McCaffrey of Microsoft Research updates regression techniques and best practices ...

Whether you’re training on 1 GPU or 512 GPUs, 50MB or 10TB of data - Composer is built to keep your workflow simple. FSDP: For large models that are too large to fit on GPUs, Composer has integrated ...

This is a PyTorch implementation of Future Data Helps Training: Modelling Future Contexts for Session-based Recommendation. To capture the sequential dependencies, existing session-based recommender ...

The final outcome of training any machine learning or deep learning algorithm is a model file that represents the mapping of input data to output predictions in an efficient manner. These models are ...

In this article, we will employ the AlexNet model provided by the PyTorch as a transfer learning framework with pre-trained ImageNet weights. The network will be trained on the CIFAR-10 dataset for a ...

The open source PyTorch machine learning (ML) framework is widely used today for AI training, but that’s not all it can do. IBM sees broader applicability for PyTorch and is working on a series ...

Despite sanctions, Chinese companies are forging ahead with AI. The Huawei AI stack is optimised to run on the CloudMatrix 384 AI chip cluster.