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# Ultralytics HUB Quickstart

Ultralytics HUB is designed to be user-friendly and intuitive, allowing users to quickly upload their datasets and train new YOLO models. It also offers a range of pre-trained models to choose from, making it extremely easy for users to get started. Once a model is trained, it can be effortlessly previewed in the Ultralytics HUB App before being deployed for real-time classification, object detection, and instance segmentation tasks.

Watch: How to train Ultralytics YOLO11 on Custom Dataset using Ultralytics HUB | HUB Datasets 🚀

## Get Started

Ultralytics HUB offers a variety of easy signup options. You can register and log in using your Google, Apple, or GitHub accounts, or simply with your email address.

During the signup, you will be asked to complete your profile.

Tip

You can update your profile from the Account tab on the Settings page.

## Home

After signing in, you will be directed to the Home page of Ultralytics HUB, which provides a comprehensive overview, quick links, and updates.

The sidebar conveniently offers links to important modules of the platform, such as Datasets, Projects, and Models.

### Recent

You can easily search globally or directly access your last updated Datasets, Projects, or Models using the Recent card on the Home page.

### Upload Dataset

You can upload a dataset directly from the Home page. Ultralytics HUB supports various dataset formats and makes it easy to prepare your data for training custom YOLO models.

Read more about datasets and how to prepare them for optimal training results.

### Create Project

You can create a project directly from the Home page. Projects help you organize related models and experiments in one place, making it easier to track progress and compare results.

Read more about projects and how they can streamline your workflow.

### Train Model

You can train a model directly from the Home page. Ultralytics HUB offers multiple training options including cloud training, Google Colab integration, or using your own hardware.

Read more about models and the various architectures available for your computer vision tasks.

## Feedback

We value your feedback! Feel free to leave a review at any time to help us improve the platform.

Info

Only our team will see your feedback, and we will use it to improve our platform.

## Need Help?

If you encounter any issues or have questions, we're here to assist you.

You can report a bug, request a feature, or ask a question on GitHub.

Note

When reporting a bug, please include your Environment Details from the Support page.

Tip

You can join our Discord community for questions and discussions!

📅 Created 1 year ago ✏️ Updated 6 months ago

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