Microsoft Azure AI Fundamentals (AI-900) Practice Exam

The identification of handwritten letters is primarily accomplished through the use of computer vision technology. Computer vision is an interdisciplinary field that enables computers to interpret and make decisions based on visual data, such as images or videos. Specifically, in the context of recognizing handwritten characters, computer vision techniques can analyze the pixel patterns in the images of handwritten text, extracting features that are essential for understanding and classifying those characters.

By applying machine learning algorithms within the computer vision framework, models can be trained on large datasets of handwritten letters. This allows the systems to learn the various shapes, strokes, and patterns associated with different letters, leading to improved accuracy in recognition tasks. Computer vision encompasses various processes, including image preprocessing, feature extraction, and applying classification algorithms, all of which contribute to successfully identifying handwritten letters.

In contrast, natural language processing focuses more on the interactions between computers and human language in textual form, making it less suitable for tasks that involve interpreting visual representations of letters. Anomaly detection, on the other hand, is used for identifying outliers or abnormal patterns in data rather than recognizing specific characters. Lastly, while machine learning techniques like regression can be applied to various predictive tasks, they are not specifically designed for image recognition tasks like identifying handwritten letters.