TensorFlow 2 quickstart for beginners | TensorFlow Core
Aug 16, 2024 · Python programs are run directly in the browser—a great way to learn and use TensorFlow. To follow this tutorial, run the notebook in Google Colab by clicking the button at …
Tutorials - TensorFlow Core
Sep 19, 2023 · Complete, end-to-end examples to learn how to use TensorFlow for ML beginners and experts. Try tutorials in Google Colab - no setup required.
Convolutional Neural Network (CNN) | TensorFlow Core
Aug 16, 2024 · This tutorial demonstrates training a simple Convolutional Neural Network (CNN) to classify CIFAR images. Because this tutorial uses the Keras Sequential API, creating and …
Working with RNNs | TensorFlow Core
Nov 16, 2023 · Here is a simple example of a Sequential model that processes sequences of integers, embeds each integer into a 64-dimensional vector, then processes the sequence of …
Image classification | TensorFlow Core
Apr 3, 2024 · This tutorial showed how to train a model for image classification, test it, convert it to the TensorFlow Lite format for on-device applications (such as an image classification app), …
TensorFlow basics | TensorFlow Core
Oct 3, 2024 · This guide provides a quick overview of TensorFlow basics. Each section of this doc is an overview of a larger topic—you can find links to full guides at the end of each section.
Training a neural network on MNIST with Keras - TensorFlow
Oct 4, 2025 · This simple example demonstrates how to plug TensorFlow Datasets (TFDS) into a Keras model.
Basic classification: Classify images of clothing - TensorFlow
Aug 16, 2024 · It's okay if you don't understand all the details; this is a fast-paced overview of a complete TensorFlow program with the details explained as you go. This guide uses tf.keras, a …
Basic regression: Predict fuel efficiency | TensorFlow Core
Jul 12, 2024 · To do this, you will provide the models with a description of many automobiles from that time period. This description includes attributes like cylinders, displacement, horsepower, …
tf.keras.layers.SimpleRNN | TensorFlow v2.16.1
Example: inputs = np.random.random((32, 10, 8)) simple_rnn = keras.layers.SimpleRNN(4) output = simple_rnn(inputs) # The output has shape `(32, 4)`. simple_rnn = keras.layers.SimpleRNN( …