How can I perform advanced preprocessing with TensorFlow.js?
You can use TensorFlow.js to perform advanced preprocessing by utilizing the tf.data
API, which allows you to create complex input pipelines.
What are some common preprocessing techniques I can implement?
Common techniques include normalization, data augmentation, and one-hot encoding, which can enhance model performance.
Can you show me an example of data augmentation?
Sure! You can use the tf.image
module to apply transformations like rotation, flipping, and scaling to your images.
How do I integrate these preprocessing steps into my model training?
You can chain your preprocessing functions in the tf.data
pipeline and then pass the dataset to the model's fit
method.
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