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Add https://youtu.be/6bZeCs0xwO4 to docs (#18292)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Muhammad Rizwan Munawar 2024-12-18 23:58:49 +05:00 • committed by GitHub
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docs/en/datasets/classify/cifar100.md
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@ -8,6 +8,17 @@ keywords: CIFAR-100, dataset, machine learning, computer vision, image classific
The [CIFAR-100](https://www.cs.toronto.edu/~kriz/cifar.html) (Canadian Institute For Advanced Research) dataset is a significant extension of the CIFAR-10 dataset, composed of 60,000 32x32 color images in 100 different classes. It was developed by researchers at the CIFAR institute, offering a more challenging dataset for more complex machine learning and [computer vision](https://www.ultralytics.com/glossary/computer-vision-cv) tasks.
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/6bZeCs0xwO4"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> How to Train Ultralytics YOLO11 on CIFAR-100 | Step-by-Step Image Classification Tutorial 🚀
</p>
## Key Features
- The CIFAR-100 dataset consists of 60,000 images, divided into 100 classes.