Computer vision and machine learning are closely related fields, but they serve different purposes in the realm of artificial intelligence.

Computer Vision focuses on enabling machines to interpret and understand visual information from the world. This involves tasks like image recognition, object detection, and image segmentation. It uses various algorithms to process and analyze visual data, aiming to replicate the human ability to see and understand images.

Machine Learning, on the other hand, is a broader field that involves training algorithms to learn from data and make predictions or decisions. It includes techniques like supervised learning, unsupervised learning, and reinforcement learning. Machine learning can be applied to a wide range of data types, not just images.

In summary, computer vision specifically deals with visual data, while machine learning encompasses a wider range of data types and learning tasks. Machine learning techniques are often used within computer vision to improve the accuracy and efficiency of visual data analysis.

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shakkar