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After describing what deep learning and neural networks are, as well as the main architectures available for the most common DL problems (classification, regression, image recognition, sequence data) it is now time to discuss some practical aspects that have to be faced when moving from the neat and tidy world of theory to the practical applications of DNNs.

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Making It Work

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  • 发表日期：

    2026年

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  • Filippo Biscarini,
  • Nelson Nazzicari

摘要

After describing what deep learning and neural networks are, as well as the main architectures available for the most common DL problems (classification, regression, image recognition, sequence data) it is now time to discuss some practical aspects that have to be faced when moving from the neat and tidy world of theory to the practical applications of DNNs.