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  • Keras: Deep Learning for humans
    KERAS 3 0 RELEASED A superpower for ML developers Keras is a deep learning API designed for human beings, not machines Keras focuses on debugging speed, code elegance conciseness, maintainability, and deployability When you choose Keras, your codebase is smaller, more readable, easier to iterate on
  • Getting started with Keras
    Getting started with Keras Learning resources Are you a machine learning engineer looking for a Keras introduction one-pager? Read our guide Introduction to Keras for engineers Want to learn more about Keras 3 and its capabilities? See the Keras 3 launch announcement Are you looking for detailed guides covering in-depth usage of different parts of the Keras API? Read our Keras developer
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    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 You can pick the framework that suits you best, and switch from one to another based on your current goals
  • Keras 3 API documentation
    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 MobileNet, MobileNetV2, and MobileNetV3 DenseNet NasNetLarge and NasNetMobile InceptionV3 InceptionResNetV2
  • Developer guides - Keras
    Keras documentation: Developer guides Developer guides Our developer guides are deep-dives into specific topics such as layer subclassing, fine-tuning, or model saving They're one of the best ways to become a Keras expert Most of our guides are written as Jupyter notebooks and can be run in one click in Google Colab, a hosted notebook environment that requires no setup and runs in the cloud
  • Code examples - Keras
    Keras documentation: Code examples Our code examples are short (less than 300 lines of code), focused demonstrations of vertical deep learning workflows
  • About Keras 3
    About Keras 3 Keras is a deep learning API written in Python and capable of running on top of either JAX, TensorFlow, or PyTorch Keras is: Simple – but not simplistic Keras reduces developer cognitive load to free you to focus on the parts of the problem that really matter Flexible – Keras adopts the principle of progressive disclosure of complexity: simple workflows should be quick and
  • Keras Applications
    Keras Applications Keras Applications are deep learning models that are made available alongside pre-trained weights These models can be used for prediction, feature extraction, and fine-tuning Weights are downloaded automatically when instantiating a model They are stored at ~ keras models Upon instantiation, the models will be built according to the image data format set in your Keras
  • Natural Language Processing - Keras
    Keras documentation: Natural Language Processing English-to-Spanish translation with a sequence-to-sequence Transformer
  • Keras documentation: KerasHub
    KerasHub is a pretrained modeling library that aims to be simple, flexible, and fast The library provides Keras 3 implementations of popular model architectures, paired with a collection of pretrained checkpoints available on Kaggle Models Models can be used for both training and inference, on any of the TensorFlow, Jax, and Torch backends KerasHub is an extension of the core Keras API





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