Abstract: Data augmentation improves machine learning model performance by diversifying training data. Initially, manual selection of augmentation techniques was required; however, AutoAugment ...

Because machine learning with deep neural techniques has advanced quickly, our resident data scientist updates binary classification techniques and best practices based on experience over the past two ...

Deep learning is changing our lives in small and large ways every day. Whether it’s Siri or Alexa following our voice commands, the real-time translation apps on our phones, or the computer vision ...

PyTorch 1.10 is production ready, with a rich ecosystem of tools and libraries for deep learning, computer vision, natural language processing, and more. Here's how to get started with PyTorch.

Data plays a foundational role in the development of machine learning models, and data augmentation techniques are a powerful way to increase the amount and diversity of data, reduce overfitting, and ...

In the document, it is said that: [...] If the image is torch Tensor, it should be of type torch.uint8, and it is expected to have […, 1 or 3, H, W] shape, where … means an arbitrary number of leading ...

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...