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 ...

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 ...

Transforms the result of TensorFlow computations.

The beginner tutorial demonstrates how to prepare data, train, and evaluate (Random Forest, Gradient Boosted Trees and CART) classifiers and regressors using TensorFlow's Decision Forests. (We'll ...

The following notebooks are available: ...

This tutorial will discuss the recommended best practices for random noise generation in TFF. Random noise generation is an important component of many privacy protection techniques in federated ...

教學課程會示範如何使用 TensorFlow.js，內容包含完整的端對端範例。 參與社群 ...

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 ...

Kubeflow is an open source ML platform dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Kubeflow Pipelines is part of the Kubeflow ...

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コレクションでコンテンツを整理 必要に応じて、コンテンツの保存と分類を行います。 Google I/O から最新の ML イノベーションを発見する Google I/O からの機械学習の新機能 最新の ML ...

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 ...