Transforms the result of TensorFlow computations.

This tutorial demonstrates how to classify structured data, such as tabular data, using a simplified version of the PetFinder dataset from a Kaggle competition stored in a CSV file. You will use Keras ...

This document is the first in a two-part series that explores the topic of data engineering and feature engineering for machine learning (ML), with a focus on supervised learning tasks. This first ...

This guide is for the latest stable version of TensorFlow. For the preview build (nightly), use the pip package named tf-nightly. Refer to these tables for older TensorFlow version requirements. For ...

Your data comes in many shapes; your tensors should too. Ragged tensors are the TensorFlow equivalent of nested variable-length lists. They make it easy to store and process data with non-uniform ...

Before you start, please run the following to make sure that your environment is correctly setup. If you don't see a greeting, please refer to the Installation guide ...

FLEURS is the speech version of the FLORES machine translation benchmark, covering 2000 n-way parallel sentences in n=102 languages. XTREME-S covers four task families: speech recognition, ...

TFX is a Google-production-scale machine learning (ML) platform based on TensorFlow. It provides a configuration framework and shared libraries to integrate common components needed to define, launch, ...

Trainer emits: At least one model for inference/serving (typically in SavedModelFormat) and optionally another model for eval (typically an EvalSavedModel). We provide support for alternate model ...

ML Metadata (MLMD) is a library for recording and retrieving metadata associated with ML developer and data scientist workflows. MLMD is an integral part of TensorFlow Extended (TFX), but is designed ...

This tutorial demonstrates text classification starting from plain text files stored on disk. You'll train a binary classifier to perform sentiment analysis on an IMDB dataset. At the end of the ...

This tutorial builds on the concepts in the Federated Learning for Image Classification tutorial, and demonstrates several other useful approaches for federated learning. In particular, we load a ...