AI-900 Question 103
Select 3A company is building a computer vision application to classify images of damaged vehicles for insurance claims. They are considering using deep learning techniques. Which of the following are key features of deep learning that make it suitable for this scenario?
- A
Ability to automatically extract features from raw data, such as images.
- B
Requires only structured data in tabular format for optimal performance.
- C
Uses multiple layers of neural networks to model complex patterns in data.
- D
Reduces the need for large datasets compared to traditional machine learning methods.
- E
Performs well in tasks like image recognition, speech processing, and natural language understanding.
Show answer and explanation
Correct answers: A, C, E
Explanation
Deep learning is particularly well-suited for scenarios involving unstructured data, such as image classification, because it can automatically extract features and model complex patterns through multiple layers of neural networks. Additionally, its proven performance in tasks like image recognition makes it a strong choice for the given use case.
- A. Correct.
Deep learning models can automatically extract features from raw data, such as patterns in images, without requiring manual feature engineering. This is one of its key strengths.
- B. Incorrect.
Deep learning is not limited to structured data. It excels at working with unstructured data, such as images, audio, or text.
- C. Correct.
Deep learning leverages multiple layers of neural networks to learn hierarchical representations of data, making it highly effective for modeling complex patterns.
- D. Incorrect.
Deep learning often requires large datasets to perform well, as it needs significant data to train the numerous parameters in its models.
- E. Correct.
Deep learning techniques are highly effective for tasks that involve unstructured data, such as image recognition, speech processing, and natural language understanding, making it suitable for this scenario.