Google's TorchTPU aims to enhance TPU compatibility with PyTorch Google seeks to help AI developers reduce reliance on Nvidia's CUDA ecosystem TorchTPU initiative is part of Google's plan to attract ...

A library of open datasets for data analytics/machine learning compiled by HackerNoon. The two most widely-used open-source machine learning frameworks for training and building deep learning models ...

I'm working with your PyTorch version of this (zcemycl/PyTorch-DeepFloorplan), and is thinking if I should implement it with a ResNet50 backbone. I'm a bit new to CNNs, and is wondering if using ...

You: Have an Apple Silicon Mac (M1, M2, M1 Pro, M1 Max, M1 Ultra) and would like to set it up for data science and machine learning. This repo: Helps you install ...

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.

Abstract: While early AutoML frameworks focused on optimizing traditional ML pipelines and their hyperparameters, a recent trend in AutoML is to focus on neural architecture search. In this paper, we ...

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 ...