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By · Reviewed & last updated · Part of TensorFlow Tutorial

Welcome to the iwantcoding.com TensorFlow Tutorial. TensorFlow is Google’s end-to-end deep-learning platform. Keras is the high-level API; tf.* drops down when you need to. Train on a laptop, scale to a TPU pod, ship to the browser via TF.js or to mobile via TF Lite.

What this tutorial covers

ChapterYou will learn
TF BasicsInstall / Colab, tensors, variables, GradientTape, tf.data.
KerasSequential, Functional API, subclassing, layers, losses, optimizers, metrics, callbacks, compile / fit.
ArchitecturesMLP, CNN, RNN / LSTM, Transformer intro, transfer learning, embeddings.
Serve & ShipSave / load, TensorFlow.js, TF Lite, TF Serving, TensorBoard, distributed training.
ExamplesCheatsheet, runnable snippets, quiz, exercises, bootcamp, certificate.

Who this is for

  • ML engineers shipping production models.
  • Researchers using Colab + TPUs.
  • Mobile / web devs running on-device inference.
How to use this tutorial: read the chapter, run the example with Try it Yourself », do the exercise, then take the quiz at the bottom. Hit Mark complete when you're done — the sidebar will track your progress.

Example

Example
import tensorflow as tf
print('TF', tf.__version__, '| GPUs:', tf.config.list_physical_devices('GPU'))
Try it Yourself »

Exercise

Canonical TF alias.

import tensorflow as

Discussion

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