iT邦幫忙

第 11 屆 iT 邦幫忙鐵人賽

DAY 8
0

Learn how to

  • Measure model performance using loss functions
  • Use loss functions as the basis for gradient descent
  • Optimize gradient descent to be as efficient as possible
  • Use performance metrics to make business decisions

Defining ML Models

Mathematical functions with parameters and hyper-parameters

  • Parameter - real-valued variable that changes during model training
  • Hyper-parameter - setting that we set before training and doesn't change afterwards

上一篇
Day 07 Launching into ML
下一篇
Day 09 Optimization (cont.)
系列文
ML Study Jam Journey30

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