What is the difference between trax vs tensorflow?
Trax is a high-level interface to make it easy to apply existing models (like ResNet, LSTM, Transformer). Trax focuses almost exclusively on deep learning.
TensorFlow is a data flow computational framework that can be applied to a wide variety of problems. TensorFlow allows fine grain control over every step in the modeling process. TensorFlow is often used for deep learning, but given its flexibility it can be used for any numerical computation.