Mar 24, 2023 · Install TensorFlow with Python's pip package manager. TensorFlow 2 packages require a pip version >19.0 (or >20.3 for macOS). Official packages available for Ubuntu, Windows, and macOS.

Mar 19, 2025 · Starting with TensorFlow 2.11, you will need to install TensorFlow in WSL2, or install tensorflow or tensorflow-cpu and, optionally, try the TensorFlow-DirectML-Plugin

Instale o TensorFlow com o gerenciador de pacotes PIP do Python. Os pacotes do TensorFlow 2 exigem uma versão 19.0 ou mais recente (ou 20.3 ou mais recente para macOS) do pip. Os pacotes oficiais estão disponíveis para Ubuntu, Windows e macOS. Consulte o guia de GPU para placas ativadas para CUDA®.

TensorFlow makes it easy to create ML models that can run in any environment. Learn how to use the intuitive APIs through interactive code samples. View tutorials

Mar 19, 2025 · Build a TensorFlow pip package from the source and install it on Windows. Note: We already provide well-tested, pre-built TensorFlow packages for Windows systems. Setup for Windows. Install the following build tools to configure your Windows development environment. Install Python and the TensorFlow package dependencies

TensorFlow をシステムにインストールする方法について説明します。pip パッケージをダウンロードするか、Docker コンテナで実行する、あるいはソースからビルドします。サポートされているカードで GPU を有効にします。

瞭解如何在系統上安裝 TensorFlow。下載 pip 套件並在 Docker 容器中執行，或從原始碼開始建構。在支援的顯示卡上啟用 GPU。

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 the top of this page. In Colab, connect to a Python runtime: At …

Apr 18, 2025 · To build TensorFlow, you will need to install Bazel. Bazelisk is an easy way to install Bazel and automatically downloads the correct Bazel version for TensorFlow. For ease of use, add Bazelisk as the bazel executable in your PATH.

Sep 30, 2024 · TensorFlow has APIs available in several languages both for constructing and executing a TensorFlow graph. The Python API is at present the most complete and the easiest to use, but other language APIs may be easier to integrate into projects and may offer some performance advantages in graph execution.