Description:

This course explores the application of deep learning in pathology for white blood cell classification using the YOLOv8 algorithm. Deep learning is a powerful technique in machine learning that has revolutionized many fields, including healthcare. In the context of pathology, it enables an automated and efficient analysis of white blood cell images, aiding in the diagnosis of various diseases and conditions. This course will provide you with the knowledge and skills needed to effectively utilize deep learning techniques for white blood cell classification using YOLOv8.

Key Highlights:

• Learn the fundamentals of deep learning in pathology
• Understand the YOLOv8 algorithm for white blood cell classification
• Explore practical applications of deep learning in pathology
• Develop skills to analyze white blood cell images using YOLOv8

What you will learn:

• Learn the fundamentals of deep learning in pathology
  Gain a solid understanding of the principles and concepts behind deep learning in pathology, and its significance in white blood cell classification using YOLOv8.
• Understand the YOLOv8 algorithm for white blood cell classification
  Dive into the details of the YOLOv8 algorithm, its architecture, and how it can be applied to efficiently classify white blood cells in pathology.
• Explore practical applications of deep learning in pathology
  Discover real-world use cases and applications of deep learning in pathology, including white blood cell classification, disease diagnosis, and treatment planning.
• Develop skills to analyze white blood cell images using YOLOv8
  Learn hands-on techniques to preprocess white blood cell images, build and train YOLOv8 models, and evaluate the classification accuracy for effective analysis in pathology.