docs: minor typo updates for branding

README.md

@@ -53,9 +53,9 @@ model-index:
 </div>
 <br>
 
-[Ultralytics](https://www.ultralytics.com/) [YOLO26](https://github.com/ultralytics/ultralytics) is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. YOLO26 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification and pose estimation tasks.
+[Ultralytics](https://www.ultralytics.com/) [YOLO26](https://github.com/ultralytics/ultralytics) is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous Ultralytics YOLO versions and introduces new features and improvements to further boost performance and flexibility. Ultralytics YOLO26 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification and pose estimation tasks.
 
-We hope that the resources here will help you get the most out of YOLO. Please browse the Ultralytics <a href="https://docs.ultralytics.com/">Docs</a> for details, raise an issue on <a href="https://github.com/ultralytics/ultralytics/issues/new/choose">GitHub</a> for support, questions, or discussions, become a member of the Ultralytics <a href="https://discord.com/invite/ultralytics">Discord</a>, <a href="https://reddit.com/r/ultralytics">Reddit</a> and <a href="https://community.ultralytics.com/">Forums</a>!
+We hope that the resources here will help you get the most out of Ultralytics YOLO. Please browse the Ultralytics <a href="https://docs.ultralytics.com/">Docs</a> for details, raise an issue on <a href="https://github.com/ultralytics/ultralytics/issues/new/choose">GitHub</a> for support, questions, or discussions, become a member of the Ultralytics <a href="https://discord.com/invite/ultralytics">Discord</a>, <a href="https://reddit.com/r/ultralytics">Reddit</a> and <a href="https://community.ultralytics.com/">Forums</a>!
 
 To request an Enterprise License please complete the form at [Ultralytics Licensing](https://www.ultralytics.com/license).
 
@@ -100,17 +100,17 @@ For alternative installation methods including [Conda](https://anaconda.org/cond
 
 ### CLI
 
-YOLO may be used directly in the Command Line Interface (CLI) with a `yolo` command:
+Ultralytics YOLO may be used directly in the Command Line Interface (CLI) with a `yolo` command:
 
 ```bash
 yolo predict model=yolo26n.pt source='https://ultralytics.com/images/bus.jpg'
 ```
 
-`yolo` can be used for a variety of tasks and modes and accepts additional arguments, i.e. `imgsz=640`. See the YOLO [CLI Docs](https://docs.ultralytics.com/usage/cli/) for examples.
+`yolo` can be used for a variety of tasks and modes and accepts additional arguments, i.e. `imgsz=640`. See the Ultralytics YOLO [CLI Docs](https://docs.ultralytics.com/usage/cli/) for examples.
 
 ### Python
 
-YOLO may also be used directly in a Python environment, and accepts the same [arguments](https://docs.ultralytics.com/usage/cfg/) as in the CLI example above:
+Ultralytics YOLO may also be used directly in a Python environment, and accepts the same [arguments](https://docs.ultralytics.com/usage/cfg/) as in the CLI example above:
 
 ```python
 from ultralytics import YOLO
@@ -137,13 +137,13 @@ results[0].show()
 path = model.export(format="onnx")  # return path to exported model
 ```
 
-See YOLO [Python Docs](https://docs.ultralytics.com/usage/python/) for more examples.
+See Ultralytics YOLO [Python Docs](https://docs.ultralytics.com/usage/python/) for more examples.
 
 </details>
 
 ## <div align="center">Models</div>
 
-YOLO26 [Detect](https://docs.ultralytics.com/tasks/detect/), [Segment](https://docs.ultralytics.com/tasks/segment/) and [Pose](https://docs.ultralytics.com/tasks/pose/) models pretrained on the [COCO](https://docs.ultralytics.com/datasets/detect/coco/) dataset are available here, as well as YOLO26 [Classify](https://docs.ultralytics.com/tasks/classify/) models pretrained on the [ImageNet](https://docs.ultralytics.com/datasets/classify/imagenet/) dataset. [Track](https://docs.ultralytics.com/modes/track/) mode is available for all Detect, Segment and Pose models.
+Ultralytics YOLO26 [Detect](https://docs.ultralytics.com/tasks/detect/), [Segment](https://docs.ultralytics.com/tasks/segment/) and [Pose](https://docs.ultralytics.com/tasks/pose/) models pretrained on the [COCO](https://docs.ultralytics.com/datasets/detect/coco/) dataset are available here, as well as Ultralytics YOLO26 [Classify](https://docs.ultralytics.com/tasks/classify/) models pretrained on the [ImageNet](https://docs.ultralytics.com/datasets/classify/imagenet/) dataset. [Track](https://docs.ultralytics.com/modes/track/) mode is available for all Detect, Segment and Pose models.
 
 <img width="1024" src="https://raw.githubusercontent.com/ultralytics/assets/main/im/banner-tasks.png" alt="Ultralytics YOLO supported tasks">
 
@@ -246,7 +246,7 @@ Our key integrations with leading AI platforms extend the functionality of Ultra
 
 | <a href="https://platform.ultralytics.com/ultralytics/yolo26"><img src="https://github.com/ultralytics/assets/raw/main/partners/logo-ultralytics-hub.png" width="40%" alt="Ultralytics Platform logo"></a><br>Ultralytics Platform 🌟 | <a href="https://docs.ultralytics.com/integrations/weights-biases/"><img src="https://github.com/ultralytics/assets/raw/main/partners/logo-wb.png" width="40%" alt="Weights & Biases logo"></a><br>Weights & Biases | <a href="https://docs.ultralytics.com/integrations/comet/"><img src="https://github.com/ultralytics/assets/raw/main/partners/logo-comet.png" width="40%" alt="Comet ML logo"></a><br>Comet | <a href="https://docs.ultralytics.com/integrations/neural-magic/"><img src="https://github.com/ultralytics/assets/raw/main/partners/logo-neuralmagic.png" width="40%" alt="Neural Magic logo"></a><br>Neural Magic |
 | :---: | :---: | :---: | :---: |
-| Streamline YOLO workflows: Label, train, and deploy effortlessly with [Ultralytics Platform](https://platform.ultralytics.com/ultralytics/yolo26). Try now! | Track experiments, hyperparameters, and results with [Weights & Biases](https://docs.ultralytics.com/integrations/weights-biases/). | Free forever, [Comet ML](https://docs.ultralytics.com/integrations/comet/) lets you save YOLO models, resume training, and interactively visualize predictions. | Run YOLO inference up to 6x faster with [Neural Magic DeepSparse](https://docs.ultralytics.com/integrations/neural-magic/). |
+| Streamline Ultralytics YOLO workflows: Label, train, and deploy effortlessly with [Ultralytics Platform](https://platform.ultralytics.com/ultralytics/yolo26). Try now! | Track experiments, hyperparameters, and results with [Weights & Biases](https://docs.ultralytics.com/integrations/weights-biases/). | Free forever, [Comet ML](https://docs.ultralytics.com/integrations/comet/) lets you save Ultralytics YOLO models, resume training, and interactively visualize predictions. | Run Ultralytics YOLO inference up to 6x faster with [Neural Magic DeepSparse](https://docs.ultralytics.com/integrations/neural-magic/). |
 
 ## <div align="center">Contribute</div>