iT邦幫忙

第 11 屆 iT 邦幫忙鐵人賽

DAY 29
0

Intro to TensorFlow

Cloud Machine Learning Engine

  • Train, deploy, and productionalize ML models at scale

Estimators

  • Interchangeable
  • Test many standard pre-made estimator models in quick succession

Checkpoints


Feature Engineering

Scale to large datasets

Find good features

Preprocessing


Art and Science of Machine Learning

Parameter Norm Penalties

  • L1 / L2 regularization
  • Max-norm regularization

Hyperparameter Tuning

  • ML models - Functions with parameters and hyper-parameters
  • Sensitive to batch size and learning rate (dataset-dependent)

Logistic Regression

  • Use Cross Entropy typically

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Day 28 Summary
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Day 30 Summary (cont.)
系列文
ML Study Jam Journey30

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