



Can 'n' represent the number of layers in a deep neural network?
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what is n in big o notation
- Can 'n' represent the number of data items in the stream?
- Is 'n' always considered in the context of asymptotic behavior?
- How does 'n' behave for very small input sizes?
- Is 'n' consistent in its use for analyzing both sequential and concurrent algorithms?
- How does 'n' relate to the stability of numerical algorithms?
- Can 'n' represent the size of the output that the algorithm produces?
- Is 'n' used in the analysis of quantum algorithms?
- Is 'n' relevant for algorithms that have a fixed runtime regardless of the input?
- Can constant factors or lower-order terms dominate for small 'n'?
- Is 'n' consistent in its meaning when analyzing different aspects of an algorithm (e.g., time complexity vs. space complexity)?
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