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AI Features

Splitting Datasets

Explore how to effectively split your dataset into training and evaluation sets in TensorFlow-based machine learning projects. Understand the importance of shuffling data to remove systematic trends and how to balance data proportions for accurate training and reliable evaluation outcomes.

Chapter Goals:

  • Learn about training and evaluation sets
  • Split the project’s final dataset into training and evaluation sets

A. Training and evaluation

There are two main components in creating a machine learning model: training and evaluation. Training is the foundation of machine learning, but evaluation is just as important. Model evaluation gives us a concrete idea of just how good the ...