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  • All (20292) +229
    • AI (3103) +13
    • DevOps (906) +6
    • Software (10480) +161
    • IT (5755) +49
    • Education (48)
  • Notice
  • All (20292) +229
  • AI (3103) +13
  • DevOps (906) +6
  • Software (10480) +161
  • IT (5755) +49
  • Education (48)
  • Notice
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  • 3周前 · ai

    ML模型:为什么你的预测是好的……直到它不是

    文章图片https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazo...

    #machine learning #feature engineering #ML pipelines #model evaluation #business metrics #data science #production ML #model monitoring
  • 1个月前 · ai

    Bias–Variance Tradeoff — 直观与实用解释(第6部分)

    偏差到底是什么意思 实际定义:偏差是指你的模型平均有多错误,因为它未能学习到真实模式。高偏差发生在:- …

    #bias-variance tradeoff #overfitting #underfitting #machine learning #model evaluation #regularization #production ML
  • 1个月前 · ai

    为什么 Accuracy 说谎 — 实际重要的指标(第4部分)

    封面图片:Why Accuracy Lies — The Metrics That Actually Matter 第4部分 https://media2.dev.to/dynamic/image/width=1000,height=420,fit=cover,gravity=auto,for...

    #accuracy #machine-learning-metrics #model-evaluation #production-ml #data-science
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