The Data Science Lab. Multi-Class Classification Using New PyTorch Best Practices, Part 2: Training, Accuracy, Predictions. Following new best practices, Dr. James McCaffrey of Microsoft Research ...

After identifying the best multiclass classification algorithm and saving the trained model, the AutoML tools created two Visual Studio projects in a subdirectory named EmpClassifier. The first ...

Multi-Class Classification Using PyTorch: Model Accuracy. Dr. James McCaffrey of Microsoft Research continues his four-part series on multi-class classification, designed to predict a value that can ...

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 ...

Often when you start learning about classification problems in Machine Learning, you start with binary classification or where there are only two possible outcomes, such as spam or not spam, fraud or ...

Fine-tuned Transfer Learning Models for Multi-class Classification of Melanoma Skin Cancer Abstract: Melanoma skin cancer is the deadliest disease that needs detection and treatment at early stages.

Multi-Class fNIRS Classification Using an Ensemble of GNN-Based Models Abstract: Functional near-infrared ... The best-performing baseline model achieved an average ternary classification accuracy of ...