The TensorFlow tutorials are written as Jupyter notebooks and run directly in Google Colab—a hosted notebook environment that requires no setup. At the top of each tutorial, you'll see a Run in Google Colab button. Click the button to open the notebook and run the code yourself.
For beginners
The best place to start is with the user-friendly Keras sequential API. Build models by plugging together building blocks. After these tutorials, read the Keras guide.Beginner quickstart
This "Hello, World!" notebook shows the Keras Sequential API andmodel.fit.
Keras basics
This notebook collection demonstrates basic machine learning tasks using Keras.Load data
These tutorials usetf.data to load various data formats and build input pipelines.
For experts
The Keras functional and subclassing APIs provide a define-by-run interface for customization and advanced research. Build your model, then write the forward and backward pass. Create custom layers, activations, and training loops.Advanced quickstart
This "Hello, World!" notebook uses the Keras subclassing API and a custom training loop.Customization
This notebook collection shows how to build custom layers and training loops in TensorFlow.Distributed training
Distribute your model training across multiple GPUs, multiple machines or TPUs.
The Advanced section has many instructive notebooks examples, including Neural machine translation, Transformers, and CycleGAN.