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Last updated on Mar 24, 2025
  1. All
  2. Engineering
  3. Algorithms

You're explaining the complexities of algorithms to your team. How do you balance speed and accuracy?

Balancing speed and accuracy in algorithms is tricky. How do you manage it?

Algorithms Algorithms

Algorithms

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Last updated on Mar 24, 2025
  1. All
  2. Engineering
  3. Algorithms

You're explaining the complexities of algorithms to your team. How do you balance speed and accuracy?

Balancing speed and accuracy in algorithms is tricky. How do you manage it?

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Help others by sharing more (125 characters min.)
2 answers
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    Parsa Emami

    Data Scientist | ML Engineer

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    I break down complex algorithms into intuitive concepts, ensuring clarity without oversimplification. Prioritizing key insights, I focus on core logic first, then dive into technical details as needed. I use real-world examples and visual aids to enhance understanding efficiently. Encouraging questions and discussions helps maintain both speed and accuracy.

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    Alexander Berkovich

    Principal AI/ML Engineer @ Akridata | Computer Vision Expert | Top AI Voice '24

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    Start with how the algorithm is solving a problem and what system requirement its meeting. Note the required time-memory complexity you are using and what's required vs the required accuracy. For example, you have 20 [msec] to process an image, and the best trade off is using a small DL model with inference time of 15[msec] on the available GPU + 5[msec] overhead for other related actions and accuracy of 96%. Alternatives might be slower but more accurate or faster but less accurate.

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Algorithms Algorithms

Algorithms

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