'What's the difference between a Tensorflow Keras Model and Estimator?
Both Tensorflow Keras models and Tensorflow Estimators are able to train neural network models and use them to predict new data. They are both high-level APIs that sits on top of the low-level core TensorFlow API. So when should I use one over the other?
Solution 1:[1]
In my understanding, estimator is for training data on large scale and serving on production purpose, because cloud ML engine can only accept estimator.
The description below from one of tensorflow doc mentioned this:
" The Estimators API is used for training models for distributed environments. This targets industry use cases such as distributed training on large datasets that can export a model for production. "
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | Jane Li |