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  1. TensorFlow

    An end-to-end open source machine learning platform for everyone. Discover TensorFlow's flexible ecosystem of tools, libraries and community resources.

  2. Machine learning education | TensorFlow

    A 3-part series that explores both training and executing machine learned models with TensorFlow.js, and shows you how to create a machine learning model in JavaScript that executes directly in the …

  3. Introduction to TensorFlow

    TensorFlow makes it easy for beginners and experts to create machine learning models for desktop, mobile, web, and cloud. See the sections below to get started.

  4. Why TensorFlow

    Build and train models by using the high-level Keras API, which makes getting started with TensorFlow and machine learning easy. If you need more flexibility, eager execution allows for immediate …

  5. Tutorials | TensorFlow Core

    Sep 19, 2023 · Keras basics This notebook collection demonstrates basic machine learning tasks using Keras.

  6. A Neural Network Playground

    For a more detailed introduction to neural networks, Michael Nielsen’s Neural Networks and Deep Learning is a good place to start. For a more technical overview, try Deep Learning by Ian …

  7. Tools - TensorFlow

    A tool for code-free probing of machine learning models, useful for model understanding, debugging, and fairness. Available in TensorBoard and jupyter or colab notebooks.

  8. Uma plataforma completa de machine learning - TensorFlow

    Uma plataforma completa com código aberto de machine learning para todo mundo. Conheça o ecossistema flexível de ferramentas, bibliotecas e recursos da comunidade do TensorFlow.

  9. Keras: The high-level API for TensorFlow | TensorFlow Core

    Jun 8, 2023 · It provides an approachable, highly-productive interface for solving machine learning (ML) problems, with a focus on modern deep learning. Keras covers every step of the machine learning …

  10. Basics of machine learning - TensorFlow

    This book introduces ML and deep learning using TensorFlow 2.0. Completing this step will round out your introductory knowledge of ML, including expanding the platform to meet your needs.