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

Add Docs glossary links (#16448)

Browse source 
Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
This commit is contained in:
Glenn Jocher 2024-09-23 23:48:46 +02:00 • committed by GitHub
parent 8b8c25f216
commit 443fbce194
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
193 changed files with 1124 additions and 1124 deletions
Download patch file Download diff file Expand all files Collapse all files

8
docs/en/help/index.md
View file

@ -20,9 +20,9 @@ We encourage you to review these resources for a seamless and productive experie
## FAQ
### What is Ultralytics YOLO and how does it benefit my machine learning projects?
### What is Ultralytics YOLO and how does it benefit my [machine learning](https://www.ultralytics.com/glossary/machine-learning-ml) projects?
Ultralytics YOLO (You Only Look Once) is a state-of-the-art, real-time object detection model. Its latest version, YOLOv8, enhances speed, accuracy, and versatility, making it ideal for a wide range of applications, from real-time video analytics to advanced machine learning research. YOLO's efficiency in detecting objects in images and videos has made it the go-to solution for businesses and researchers looking to integrate robust computer vision capabilities into their projects.
Ultralytics YOLO (You Only Look Once) is a state-of-the-art, real-time [object detection](https://www.ultralytics.com/glossary/object-detection) model. Its latest version, YOLOv8, enhances speed, [accuracy](https://www.ultralytics.com/glossary/accuracy), and versatility, making it ideal for a wide range of applications, from real-time video analytics to advanced machine learning research. YOLO's efficiency in detecting objects in images and videos has made it the go-to solution for businesses and researchers looking to integrate robust [computer vision](https://www.ultralytics.com/glossary/computer-vision-cv) capabilities into their projects.
For more details on YOLOv8, visit the [YOLOv8 documentation](../tasks/detect.md).
@ -32,7 +32,7 @@ Contributing to Ultralytics YOLO repositories is straightforward. Start by revie
### Why should I use Ultralytics HUB for my machine learning projects?
Ultralytics HUB offers a seamless, no-code solution for managing your machine learning projects. It enables you to generate, train, and deploy AI models like YOLOv8 effortlessly. Unique features include cloud training, real-time tracking, and intuitive dataset management. Ultralytics HUB simplifies the entire workflow, from data processing to model deployment, making it an indispensable tool for both beginners and advanced users.
Ultralytics HUB offers a seamless, no-code solution for managing your machine learning projects. It enables you to generate, train, and deploy AI models like YOLOv8 effortlessly. Unique features include cloud training, real-time tracking, and intuitive dataset management. Ultralytics HUB simplifies the entire workflow, from data processing to [model deployment](https://www.ultralytics.com/glossary/model-deployment), making it an indispensable tool for both beginners and advanced users.
To get started, visit [Ultralytics HUB Quickstart](../hub/quickstart.md).
@ -42,7 +42,7 @@ Continuous Integration (CI) in Ultralytics involves automated processes that ens
Learn more in the [Continuous Integration (CI) Guide](../help/CI.md).
### How is data privacy handled by Ultralytics?
### How is [data privacy](https://www.ultralytics.com/glossary/data-privacy) handled by Ultralytics?
Ultralytics takes data privacy seriously. Our [Privacy Policy](../help/privacy.md) outlines how we collect and use anonymized data to improve the YOLO package while prioritizing user privacy and control. We adhere to strict data protection regulations to ensure your information is secure at all times.