Add https://youtu.be/R42s2zFtNIY to `hub/datasets.md` and CoreML image fix (#8085)

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

docs/en/hub/datasets.md

@@ -10,6 +10,17 @@ keywords: Ultralytics, HUB datasets, YOLO model training, upload datasets, datas
 
 Once uploaded, datasets can be immediately utilized for model training. This integrated approach facilitates a seamless transition from dataset management to model training, significantly simplifying the entire process.
 
+<p align="center">
+  <br>
+  <iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/R42s2zFtNIY"
+    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> Watch: Upload Datasets to Ultralytics HUB | Complete Walkthrough of Dataset Upload Feature
+</p>
+
 ## Upload Dataset
 
 Ultralytics HUB datasets are just like YOLOv5 and YOLOv8 🚀 datasets. They use the same structure and the same label formats to keep everything simple.

docs/en/integrations/coreml.md

@@ -13,7 +13,7 @@ The CoreML export format allows you to optimize your [Ultralytics YOLOv8](https:
 ## CoreML
 
 <p align="center">
-  <img width="100%" src="https://docs-assets.developer.apple.com/published/b8a49e3417/renderedDark2x-1638462887.png" alt="CoreML Overview">
+  <img width="100%" src="https://github.com/RizwanMunawar/ultralytics/assets/62513924/0c757e32-3a9f-422e-9526-efde5f663ccd" alt="CoreML Overview">
 </p>
 
 [CoreML](https://developer.apple.com/documentation/coreml) is Apple's foundational machine learning framework that builds upon Accelerate, BNNS, and Metal Performance Shaders. It provides a machine-learning model format that seamlessly integrates into iOS applications and supports tasks such as image analysis, natural language processing, audio-to-text conversion, and sound analysis.

docs/en/integrations/gradio.md

@@ -16,7 +16,9 @@ This Gradio interface provides an easy and interactive way to perform object det
 * **Real-Time Adjustments:** Parameters such as confidence and IoU thresholds can be adjusted on the fly, allowing for immediate feedback and optimization of detection results.
 * **Broad Accessibility:** The Gradio web interface can be accessed by anyone, making it an excellent tool for demonstrations, educational purposes, and quick experiments.
 
-<img width="800" alt="Gradio example screenshot" src="https://github.com/WangQvQ/ultralytics/assets/58406737/5d906f10-fd62-4bcc-8856-ef3233102c1d">
+<p align="center">
+   <img width="800" alt="Gradio example screenshot" src="https://github.com/RizwanMunawar/ultralytics/assets/26833433/52ee3cd2-ac59-4c27-9084-0fd05c6c33be">
+</p>
 
 ## How to Install the Gradio