NCA-AIIO Question 15
Select 3A data scientist is tasked with building a solution to automatically classify images of animals into categories (e.g., cat, dog, bird). They are debating between traditional machine learning approaches and deep learning approaches. Which statements correctly differentiate between machine learning and deep learning in this context?
- A
Machine learning typically requires manual feature extraction, while deep learning automates feature extraction using neural networks.
- B
Deep learning is a subset of machine learning that uses algorithms like decision trees and support vector machines to train models.
- C
Deep learning models generally require more computational resources compared to traditional machine learning models.
- D
Machine learning models can outperform deep learning when there is limited labeled data available.
- E
Deep learning is not suitable for image classification tasks due to its limited performance in handling complex data.
Show answer and explanation
Correct answers: A, C, D
Explanation
Machine learning and deep learning are closely related but have distinct characteristics. Machine learning requires manual feature engineering, while deep learning automates this process using neural networks. Deep learning is resource-intensive and performs well on large datasets, particularly for tasks like image classification, but may not be optimal for small datasets. Understanding these differences helps in selecting the appropriate approach for specific use cases.
- A. Correct.
Correct: Machine learning models usually require manual feature extraction, whereas deep learning models leverage neural networks to automatically learn features from raw data.
- B. Incorrect.
Incorrect: Deep learning is a subset of machine learning, but it does not use traditional algorithms like decision trees or support vector machines. It relies on neural networks.
- C. Correct.
Correct: Deep learning models, due to their complexity and the use of large neural networks, typically require significantly more computational resources.
- D. Correct.
Correct: Traditional machine learning models often perform better than deep learning models when the dataset is small, as deep learning requires large amounts of labeled data for optimal performance.
- E. Incorrect.
Incorrect: Deep learning is highly suitable for image classification tasks and often excels in handling complex data like images.