iT邦幫忙

第 11 屆 iT 邦幫忙鐵人賽

DAY 30
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Art and Science of Machine Learning

Neural Networks

  • Linear Model can be represented as nodes and edges
  • Non-Linear Transformation (aka Activation Function)

Custom Estimator

  • Modeling
  • Checkpointing
  • Memory size
  • Training, evaluating
  • Adjust hyper parameter

Keras Models

  • High-level deep neural networks library (supports multiple backends)
  • Fast prototyping

上一篇
Day 29 Summary (cont.)
系列文
ML Study Jam Journey30

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