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TensorFlow

An end-to-end machine learning platform.

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This course has 3 lessons. Start with the first one and use the next / previous links at the bottom of each lesson — the sidebar keeps the whole course in order.

Lessons

  1. Tensors and eager executionImmutable constants, trainable variables, shape and dtype rules, and how tf.function turns Python into a traced graph.
  2. Building a Keras modelSequential and functional APIs, matching the output layer and loss to the task, and the from_logits setting that silently costs you accuracy.
  3. Training, saving and servingmodel.fit with callbacks, a custom GradientTape loop, the tf.data pipeline, and exporting a model whose preprocessing travels with it.

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Last refreshed 2026-09-17.