How to Train Ultralytics YOLOv8 Models on Your Custom Dataset | 196 classes | Image classification

This Reddit post highlights a tutorial on training Ultralytics YOLOv8 for image classification using a custom dataset. Specifically, it focuses on classifying 196 different car categories using the Stanford Cars dataset. The tutorial provides a comprehensive guide, covering environment setup, data preparation, model training, and testing. The inclusion of both video and written explanations with code makes it accessible to a wide range of learners, from beginners to more experienced practitioners. The author emphasizes its suitability for students and beginners in machine learning and computer vision, offering a practical way to apply theoretical knowledge. The clear structure and readily available resources enhance its value as a learning tool.

• •Learn to train YOLOv8 for image classification on custom datasets.
• •Utilize the Stanford Cars dataset for a practical project.
• •Access both video and written tutorials for comprehensive learning.