<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Pytorch on Neural Odyssey</title><link>https://danialjfz.github.io/myblog/tags/pytorch/</link><description>Recent content in Pytorch on Neural Odyssey</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>Danialj999@gmail.com (Danial Jafarzadeh)</managingEditor><webMaster>Danialj999@gmail.com (Danial Jafarzadeh)</webMaster><copyright>© 2026 Danial Jafarzadeh</copyright><lastBuildDate>Tue, 18 Nov 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://danialjfz.github.io/myblog/tags/pytorch/index.xml" rel="self" type="application/rss+xml"/><item><title>Build Your First ML Model: A No-BS Guide</title><link>https://danialjfz.github.io/myblog/posts/build-your-first-ml-model/</link><pubDate>Tue, 18 Nov 2025 00:00:00 +0000</pubDate><author>Danialj999@gmail.com (Danial Jafarzadeh)</author><guid>https://danialjfz.github.io/myblog/posts/build-your-first-ml-model/</guid><description>&lt;blockquote&gt;
&lt;p&gt;&lt;strong&gt;Abstract&lt;/strong&gt;&lt;br&gt;
This post walks through a first end-to-end ML workflow using a real image classification task. The goal is not just to train a model, but to build the habits that matter in practice: checking data, splitting correctly, choosing a simple baseline, and evaluating results without fooling yourself.&lt;/p&gt;</description></item></channel></rss>