Individual skill
tensorflow-pro
TensorFlow/Keras guidance — model building, tf.data pipelines, training, SavedModel, TF Serving, and TFLite.
skills/tensorflow-pro/SKILL.md
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## Overview
TensorFlow (with Keras as its high-level API) is the production-oriented deep learning framework: strong serving story (TF Serving, TFLite, TF.js), `tf.data` pipelines, and broad deployment targets from servers to phones to browsers. Keras 3's multi-backend design (TensorFlow/JAX/PyTorch) makes model code portable in a way the ecosystem hasn't had before.
This skill covers the modern TF/Keras workflow: building models with the Functional/Sequential APIs, efficient `tf.data` pipelines, training with `fit()` and custom loops, exporting SavedModels, and deploying via TF Serving and TFLite.
## When to use
- Building models with Keras (Functional or Sequential API).
- Writing efficient `tf.data` input pipelines.
- Training with `fit()` vs custom training loops.
- Exporting SavedModel and serving with TF Serving.
- Deploying to mobile/edge with TFLite.
- Choosing between TensorFlow, PyTorch, and JAX.