Microsoft Azure AI Fundamentals AI-900 Practice Question
A data scientist is tasked with developing a model to recognize and classify images of handwritten letters from thousands of samples with varying handwriting styles.
Which feature of deep learning techniques makes them particularly suitable for this task?
Their effectiveness when working with small datasets
Their dependence on manual feature extraction methods
Their minimal computational resource requirements during training
Their ability to automatically learn complex patterns and features from raw data like images
Deep learning techniques have the capability to automatically learn complex patterns and features from raw data like images. This ability eliminates the need for manual feature engineering, allowing the model to identify intricate patterns within the data that may be difficult to extract manually.
The other options are incorrect because deep learning models typically require substantial computational resources and large datasets to perform effectively. Additionally, they do not depend on manual feature extraction methods.
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Microsoft Azure AI Fundamentals AI-900
Describe Fundamental Principles of Machine Learning on Azure
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