iT邦幫忙

第 11 屆 iT 邦幫忙鐵人賽

DAY 4
0

Summary

  1. AI first
  2. Create good ML datasets, then building your first ML model with TensorFlow
  3. Improving ML accuracy
  4. ML at scale
  5. Specialized ML models
    • Image classification models
    • Sequence models
    • Recommendation systems

Two stages of ML

  1. Train an ML model with examples (Training)
    • label - true answer
    • model - mathematical function
  2. Predict with a trained model (Inference)

Adjust function so that outputs of model for set of training inputs is as close as possible to the training labels


上一篇
Day 03 Introduction (cont.)
下一篇
Day 05 Introduction (cont.)
系列文
ML Study Jam Journey29

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