Learn the key differences between deep learning and classical machine learning approaches. Prepare for the IBM Artificial Intelligence Fundamentals certification exam.
Table of Contents
Question
Complete the sentence. Deep learning can be differentiated from classical machine learning in that deep learning exclusively uses _______________.
A. linear regression
B. reinforcement learning
C. decision trees
D. artificial neural networks
Answer
D. artificial neural networks
Deep learning can be differentiated from classical machine learning in that deep learning exclusively uses artificial neural networks.
Explanation
Deep learning is characterized by artificial neural networks, which consist of multiple layers of interconnected nodes inspired by the operation of neural networks in the human brain.
Deep learning is a subset of machine learning that relies solely on artificial neural networks, which are loosely modeled on the structure and function of the human brain. These networks consist of multiple layers of interconnected nodes that process and learn from data.
In contrast, classical machine learning encompasses a broader range of algorithms and techniques, including but not limited to:
- Linear regression: A statistical method for modeling the relationship between variables.
- Decision trees: A tree-like model that makes decisions based on input features.
- Reinforcement learning: A technique where an agent learns to make decisions by interacting with an environment and receiving rewards or penalties.
While these classical approaches can be effective for certain tasks, deep learning has proven particularly powerful for complex problems like image and speech recognition, natural language processing, and more. The multi-layered structure of deep neural networks allows them to automatically learn hierarchical representations of data, enabling them to capture intricate patterns and abstractions.
So in summary, the key differentiator of deep learning is its exclusive reliance on artificial neural networks, setting it apart from the diverse array of algorithms used in classical machine learning.
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