Keras documentation.

Keras documentation Keras — это библиотека глубокого обучения, представляющая из себя высокоуровневый API, написанный на Python и способный работать поверх TensorFlow, Theano Jun 18, 2021 · Pour commencer à utiliser Keras, vous pouvez tout d’abord lire la documentation officielle, explorer le dépôt de code sur GitHub, installer Keras et un moteur backend comme TensorFlow. keras. keras format and two legacy formats: SavedModel, and HDF5). ^ Keras 2. Learn how to use the Keras module in TensorFlow, a high-level API for building and training deep learning models. py file that follows a specific format. layers. io. Getting started Developer guides Code examples Keras 3 API documentation Keras 2 API documentation Models API Layers API Callbacks API Optimizers Metrics Losses Data loading Built-in small datasets Keras Applications Mixed precision Utilities KerasTuner: Hyperparam Tuning KerasHub: Pretrained Models KerasRS Keras: La librairie de Deep Learning Python. Sequential API. Para uma introdução ao machine learning com tf. Getting started Developer guides Code examples Keras 3 API documentation Models API Layers API Callbacks API Ops API Optimizers Metrics Losses Data loading Built-in small datasets Keras Applications Mixed precision Multi-device distribution RNG API Rematerialization Utilities Keras 2 API documentation KerasTuner: Hyperparam Tuning KerasHub See full list on keras. Author: fchollet Date created: 2019/03/20 Last modified: 2020/04/20 Description: Image segmentation model trained from scratch on the Oxford Pets dataset. Keras is designed to quickly define deep learning models. LSTM For more information, see the RNN API documentation. O guia Keras: uma visão geral rápida ajudará você a dar os primeiros passos. Loss instance. KerasHub is a pretrained modeling library that aims to be simple, flexible, and fast. 0 Description Interface to 'Keras' <https://keras. Keras 3 API documentation Models API Layers API The base Layer class Layer activations Layer weight initializers Layer weight regularizers Layer weight constraints Core layers Convolution layers Pooling layers Recurrent layers Preprocessing layers Normalization layers Regularization layers Attention layers Reshaping layers Merging layers Activation layers Backend-specific Keras •A python package (Python 2. 6) •Sits on top of TensorFlow or Theano (Stopped) •High-level neural network API •Runs seamlessly on CPU and GPU keras-ocr provides out-of-the-box OCR models and an end-to-end training pipeline to build new OCR models. They are usually generated from Jupyter notebooks. This website provides documentation for the R interface to Keras. （原始内容存档于2022-11-29）. Model. [2016-09-18]. io keras-team/keras-io’s past year of commit activity Jupyter Notebook 2,861 Apache-2. Keras documentationの日本語訳化 A model is an object that groups layers together and that can be trained on data. applications. ^ Chollet, François. Getting started Developer guides Code examples Keras 3 API documentation Models API Layers API The base Layer class Layer activations Layer weight initializers Layer weight regularizers Layer weight constraints Core layers Convolution layers Pooling layers Recurrent layers Preprocessing layers Normalization layers Regularization layers Mar 1, 2019 · Introduction. Star. losses. The functional API can handle models with non-linear topology, shared layers, and even multiple inputs or outputs. io>, a high-level neural networks 'API'. See the main Keras website at https://keras. loss: "auto", a loss name, or a keras. The width and height dimensions tend to shrink as you go deeper in the network. Input objects, but with the tensors that originate from keras. View in Colab • GitHub source Keras is an open-source library that provides a Python interface for artificial neural networks. losses for more info on possible loss values. Effortlessly build and train models for computer vision, natural language processing, audio processing, timeseries forecasting, recommender systems, etc. Keras is a high-level API to build and train deep learning models. Modularité et facilité de composition Les modèles Keras sont créés en connectant des composants configurables, avec quelques restrictions. Keras: библиотека глубокого обучение на Python Вы только что открыли для себя Keras. compile and keras. The Keras functional API is a way to create models that are more flexible than the keras. md sources files of keras. 为什么取名为 Keras? Keras (κέρας) 在希腊语中意为 号角 。 它来自古希腊和拉丁文学中的一个文学形象，首先出现于 《奥德赛》 中， 梦神 (Oneiroi, singular Oneiros) 从这两类人中分离出来：那些用虚幻的景象欺骗人类，通过象牙之门抵达地球之人，以及那些宣告未来即将到来，通过号角之门抵达之人。 New examples are added via Pull Requests to the keras. Elle fournit des informations claires et concrètes concernant les erreurs des utilisateurs. Learn how to use Keras with its multi-backend approach, developer guides, examples, and KerasHub library of pretrained models. 0 2,090 99 25 Updated May 2, 2025 Keras documentation. For VGG16, call keras. Why this name, Keras? Keras (κέρας) means horn in Greek. 4. （原始内容存档于2020-01-17）. The purpose of Keras is to give an unfair advantage to any developer looking to ship Machine Learning-powered apps. The Keras functional API is the way to go for defining complex models, such as multi-output models, directed acyclic graphs, or models with shared layers. Vous consultez une traduction en français de la documentation de la librairie Keras réalisée par ActuIA avec l'autorisation de François Chollet, créateur de cette librairie, que nous tenons à remercier pour sa confiance. As previously announced, we have discontinued multi-backend Keras to refocus exclusively on the TensorFlow implementation of Keras. It’s used for fast prototyping, advanced research, and production, with three key advantages: User friendly – Keras has a simple, consistent interface optimized for common use cases. Package ‘keras’ April 20, 2024 Type Package Title R Interface to 'Keras' Version 2. When you choose Keras, your codebase is smaller, more readable, easier to iterate on. Keras 3 API documentation Models API Layers API The base Layer class Layer activations Layer weight initializers Layer weight regularizers Layer weight constraints Core layers Convolution layers Pooling layers Recurrent layers Preprocessing layers Normalization layers Regularization layers Attention layers Reshaping layers Merging layers Activation layers Backend-specific After five months of extensive public beta testing, we're excited to announce the official release of Keras 3. 感谢 keras-team 所做的中文翻译工作，本文档制作基于此处。 The main reason of organizing PDF version based the Chinese Keras Markdown is that it is easy to read locally when learning the Keras Deep Learning Library. Find out the core components of Keras, such as layers, models, optimizers, metrics, and more. Para una introduccion amigable a principiantes sobre aprendizaje maquina con tf. vgg16. io Jun 8, 2023 · Learn how to use Keras, the approachable and productive interface for solving machine learning problems with TensorFlow. Para saber mais sobre a API, consulte o seguinte conjunto de guias que aborda o que você precisa saber como usuário avançado da TensorFlow Keras: This means that Keras is appropriate for building essentially any deep learning model, from a memory network to a neural Turing machine. Thanks for the Chinese translation work done by keras-team, this document is produced based on it. Keras documentation. If you never set it, then it will be "tf". Aug 16, 2024 · Above, you can see that the output of every Conv2D and MaxPooling2D layer is a 3D tensor of shape (height, width, channels). La documentation originale et officielle, en anglais, peut être trouvée ici. It is a reference to a literary image from ancient Greek and Latin literature, first found in the Odyssey, where dream spirits (Oneiroi, singular Oneiros) are divided between those who deceive men with false visions, who arrive to Earth through a gate of ivory, and those who announce a future that will come to pass, who arrive KerasHub. Please see the examples for more information. Keras 3 is a multi-backend deep learning framework, with support for JAX, TensorFlow, and PyTorch. keras, ve este conjunto de tutoriales para principiantes. Getting started Developer guides Code examples Keras 3 API documentation Models API Layers API Callbacks API Ops API Optimizers Metrics Losses Data loading Built-in small datasets Keras Applications Xception EfficientNet B0 to B7 EfficientNetV2 B0 to B3 and S, M, L ConvNeXt Tiny, Small, Base, Large, XLarge VGG16 and VGG19 ResNet and ResNetV2 Getting started Developer guides Code examples Keras 3 API documentation Models API Layers API Callbacks API Ops API Optimizers Metrics Losses Data loading Built-in small datasets Keras Applications Mixed precision Multi-device distribution RNG API Rematerialization Utilities Experiment management utilities Model plotting utilities Structured It defaults to the image_dim_ordering value found in your Keras config file at ~/. io for additional information on the project. Keras documentation, hosted live at keras. Under the hood, the layers and weights will be shared across these models, so that user can train the full_model, and use backbone or activations to do feature extraction. Run the guides in Google Colab with GPU or TPU support. See the tutobooks documentation for more details. Input objects, but with the tensors that are originated from keras. 0. Contents i. ii. 深度学习与Keras：位于导航栏最下方的该模块翻译了来自Keras作者博客keras. preprocess_input on your inputs before passing them to the model. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as. Author: fchollet Date created: 2020/04/12 Last modified: 2023/06/25 Description: Complete guide to the Sequential model. Features Keras leverages various optimization techniques to make high level neural network API Getting started Developer guides Code examples Computer Vision Image classification from scratch Simple MNIST convnet Image classification via fine-tuning with EfficientNet Image classification with Vision Transformer Classification using Attention-based Deep Multiple Instance Learning Image classification with modern MLP models A mobile Note that the backbone and activations models are not created with keras. Input objects. Find classes, functions, and other members of the tf. The library provides Keras 3 implementations of popular model architectures, paired with a collection of pretrained checkpoints available on Kaggle Models. RNN, keras. optimizers for more info on possible optimizer values. keras. keras automatically saves in the latest format. keras, consulte esta série de tutoriais para iniciantes. SparseCategoricalCrossentropy loss will be applied for the classification task. Para profundizar mas en la API, consulta el siguiente conjunto de guías que cubren lo siguiente que necesitas saber como super usuario de TensorFlow Why this name, Keras? Keras (κέρας) means horn in Greek. Keras is based on minimal structure that provides a clean and easy way to create deep learning models based on TensorFlow or Theano. None Getting started Developer guides Code examples Computer Vision Natural Language Processing Text classification from scratch Review Sep 30, 2024 · API Documentation Stay organized with collections Save and categorize content based on your preferences. [2022-08-31]. Keras focuses on debugging speed, code elegance & conciseness, maintainability, and deployability. keras/keras. Keras 3 is a multi-backend deep learning framework with support for JAX, TensorFlow, PyTorch, and OpenVINO. It is a reference to a literary image from ancient Greek and Latin literature, first found in the Odyssey, where dream spirits (Oneiroi, singular Oneiros) are divided between those who deceive men with false visions, who arrive to Earth through a gate of ivory, and those who announce a future that will come to pass, who arrive Keras documentation. io Why this name, Keras? Keras (κέρας) means horn in ancient Greek. Please create a /home/docs Transfer learning & fine-tuning. Nov 16, 2023 · The Keras RNN API is designed with a focus on: Ease of use: the built-in keras. It is a reference to a literary image from ancient Greek and Latin literature, first found in the Odyssey, where dream spirits (Oneiroi, singular Oneiros) are divided between those who deceive dreamers with false visions, who arrive to Earth through a gate of ivory, and those who announce a future that will come to pass, who Keras dispose d'une interface simple et cohérente, optimisée pour les cas d'utilisation courants. Learn how to install, configure, and use Keras 3 for computer vision, natural language processing, and more. Author: fchollet Date created: 2020/04/15 Last modified: 2023/06/25 Description: Complete guide to transfer learning & fine-tuning in Keras. كيراس (بالإنجليزية Keras) هي مكتبة شبكات عصبونية مفتوحة المصدر مكتوبة بلغة بايثون . Contribute to keras-team/keras-io development by creating an account on GitHub. See keras. Keras was first independent software, then integrated into the See keras. An entire model can be saved in three different file formats (the new . keras zip archive. Metric functions are similar to loss Getting started Developer guides Code examples Keras 3 API documentation Models API Layers API The base Layer class Layer activations Layer weight initializers Layer weight regularizers Layer weight constraints Core layers Convolution layers Pooling layers Recurrent layers Preprocessing layers Normalization layers Regularization layers Apr 12, 2020 · The Sequential model. View in Colab • GitHub source Overview; ResizeMethod; adjust_brightness; adjust_contrast; adjust_gamma; adjust_hue; adjust_jpeg_quality; adjust_saturation; central_crop; combined_non_max_suppression tf. 7-3. Note that the backbone and activations models are not created with keras. TensorFlow has APIs available in several languages both for constructing and executing a TensorFlow graph. json. keras module, as well as license and version information. Mar 20, 2019 · Image segmentation with a U-Net-like architecture. Note: each Keras Application expects a specific kind of input preprocessing. Only required if featurewise_center or featurewise_std_normalization or Getting started Developer guides Code examples Keras 3 API documentation Models API The Model class The Sequential class Model training APIs Saving & serialization Layers API Callbacks API Ops API Optimizers Metrics Losses Data loading Built-in small datasets Keras Applications Mixed precision Multi-device distribution RNG API Rematerialization Getting started Developer guides Code examples Keras 3 API documentation Models API Layers API The base Layer class Layer activations Layer weight initializers Layer weight regularizers Layer weight constraints Core layers Convolution layers Pooling layers Recurrent layers Preprocessing layers Normalization layers Regularization layers Keras Documentation Release stable Dec 01, 2017. Learn how to use Keras for deep learning with these guides on topics such as layer subclassing, fine-tuning, or model saving. keras による機械学習について、入門者を対象とした概要説明がスターター チュートリアル セットに用意されています。 API の詳細については、TensorFlow Keras のパワーユーザーとして知っておくべきことを網羅した次のガイドをご覧ください。 This is the repository for the translated . The translation project. It provides clear and actionable feedback for user errors. The simplest type of model is the Sequential model, which is a linear stack of layers. En outre, vous pouvez essayer le tutoriel officiel pour le modèle Séquentiel , et explorer les différents exemples. Keras is a deep learning API designed for human beings, not machines. Keras 3 is a multi-backend deep learning framework, with support for JAX, TensorFlow, PyTorch, and OpenVINO (for inference-only). Apr 2, 2025 · Keras 3: Deep Learning for Humans. Keras Documentation, Release latest This is an autogenerated index file. If you would like to convert a Keras 2 example to Keras 3, please open a Pull Request to the keras. Keras Documentation, Release stable This is an autogenerated index file. They must be submitted as a . preprocess_input will convert the input images from RGB to BGR, then will zero-center each color channel with respect to the ImageNet dataset, without scaling. 15. Defaults to "auto", where a keras. io和其他Keras相关博客的文章，该栏目的文章提供了对深度学习的理解和大量使用Keras的例子，您也可以向这个栏目投稿。 所有的文章均在醒目位置标志标明来源与作者，本文档对该栏目 Keras 3 API documentation / Metrics Metrics. io repository. Xception: Deep Learning with Depthwise Apr 3, 2024 · Call tf. يمكن أن تعمل بالاعتماد على تنسرفلو ، أدوات ميكروسوفت الإدراكية ، لغة آر ، Theano ، أو PlaidML . Saving a model as path/to/model. Keras 3 is a full rewrite of Keras that enables you to run your Keras workflows on top of either JAX, TensorFlow, PyTorch, or OpenVINO (for inference-only), and that unlocks brand new large-scale model training and deployment capabilities. save to save a model's architecture, weights, and training configuration in a single model. A metric is a function that is used to judge the performance of your model. Methods: fit(X): Compute the internal data stats related to the data-dependent transformations, based on an array of sample data. Well, Keras is an optimal choice for deep learning applications. Keras Documentation Release latest Dec 12, 2017. Getting started Developer guides Code examples Keras 3 API documentation Models API The Model class The Sequential class Model training APIs Saving & serialization Layers API Callbacks API Ops API Optimizers Metrics Losses Data loading Built-in small datasets Keras Applications Mixed precision Multi-device distribution RNG API Rematerialization 有关最新文档，请访问 Read the Docs 备份版本：keras-zh，每月更新。 有关官方原始文档，请访问 Keras官方中文文档 。 Translation has done! La guia Keras: Una visión aápida te ayudara a empezar. vgg16. ^ Keras Documentation. Please create a /home/docs Getting started with the Keras functional API. For more complex architectures, you can either use the Keras functional API, which lets you build arbitrary graphs of layers, or use subclassing to write models from scratch. crlyyprbd gkatqs eurjh dugb ajneiz jwwua ppumcoq wbx oixlk axxcz nocwzr dxp yswvc aymkfol nohnvvy