HongChuang/ultralytics-ascend
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions 3

Add https://youtu.be/EeDd5P4eS6A to docs (#15107)

Browse source
This commit is contained in:
Muhammad Rizwan Munawar 2024-08-11 09:43:12 +05:00 • committed by GitHub
parent 93193ca592
commit d96ea5b493
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
1 changed files with 11 additions and 0 deletions
Download patch file Download diff file Expand all files Collapse all files

11
docs/en/integrations/weights-biases.md
View file

@ -8,6 +8,17 @@ keywords: YOLOv8, Weights & Biases, model training, experiment tracking, Ultraly
Object detection models like [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics) have become integral to many computer vision applications. However, training, evaluating, and deploying these complex models introduces several challenges. Tracking key training metrics, comparing model variants, analyzing model behavior, and detecting issues require substantial instrumentation and experiment management.
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/EeDd5P4eS6A"
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 use Ultralytics YOLOv8 with Weights and Biases
</p>
This guide showcases Ultralytics YOLOv8 integration with Weights & Biases' for enhanced experiment tracking, model-checkpointing, and visualization of model performance. It also includes instructions for setting up the integration, training, fine-tuning, and visualizing results using Weights & Biases' interactive features.
## Weights & Biases