<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>PyTorch - Tag - DataSci Ocean</title><link>https://datasciocean.com/en/tags/pytorch/</link><description>PyTorch - Tag - DataSci Ocean</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>l066858998@gmail.com (Hong-Wei Wu)</managingEditor><webMaster>l066858998@gmail.com (Hong-Wei Wu)</webMaster><copyright>This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</copyright><lastBuildDate>Mon, 12 Jun 2023 00:00:00 +0000</lastBuildDate><atom:link href="https://datasciocean.com/en/tags/pytorch/" rel="self" type="application/rss+xml"/><item><title>Building an Image Classifier with PyTorch's ResNet</title><link>https://datasciocean.com/en/other/pytorch-resnet-image-classifier/</link><pubDate>Mon, 12 Jun 2023 00:00:00 +0000</pubDate><author><name>Hong-Wei Wu</name></author><guid>https://datasciocean.com/en/other/pytorch-resnet-image-classifier/</guid><description>&lt;div class="featured-image">
                &lt;img src="/other/pytorch-resnet-image-classifier/featured-image.jpg" referrerpolicy="no-referrer">
            &lt;/div>Load a pretrained ResNet from PyTorch's TorchVision and classify dog, cat, and airplane photos, no training required, with runnable Colab and GitHub code.</description></item><item><title>Running PyTorch on Apple Silicon: Enabling M1 GPU Training</title><link>https://datasciocean.com/en/other/pytorch-apple-silicon-m1-gpu/</link><pubDate>Thu, 18 May 2023 00:00:00 +0000</pubDate><author><name>Hong-Wei Wu</name></author><guid>https://datasciocean.com/en/other/pytorch-apple-silicon-m1-gpu/</guid><description>&lt;div class="featured-image">
                &lt;img src="/other/pytorch-apple-silicon-m1-gpu/featured-image.jpeg" referrerpolicy="no-referrer">
            &lt;/div>A hands-on guide to enabling GPU-accelerated PyTorch training on Apple Silicon Macs, from installing Miniconda to benchmarking M1 CPU vs. GPU speed.</description></item></channel></rss>