Keyword Analysis & Research: tensorflow keras
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Keras: The high-level API for TensorFlow | TensorFlow Core
https://www.tensorflow.org/guide/keras
WebJun 8, 2023 · Keras is the high-level API of the TensorFlow platform. 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 workflow, from data processing to hyperparameter tuning to deployment.
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Getting started with Keras
https://keras.io/getting_started/
WebTo use Keras 3, you will also need to install a backend framework – either JAX, TensorFlow, or PyTorch: Installing JAX; Installing TensorFlow; Installing PyTorch; If you install TensorFlow 2.15, you should reinstall Keras 3 afterwards. The cause is that tensorflow==2.15 will overwrite your Keras installation with keras==2.15. This step is not ...
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Module: tf.keras | TensorFlow v2.16.1
https://www.tensorflow.org/api_docs/python/tf/keras
WebModule: tf.keras | TensorFlow v2.16.1. Overview Python C++ Java More. All Symbols. Python v2.16.1. tf.audio. tf.autodiff. tf.autograph. tf.bitwise. tf.compat. tf.config. tf.data. …
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Keras: Deep Learning for humans
https://keras.io/
WebKeras works with JAX, TensorFlow, and PyTorch. It enables you to create models that can move across framework boundaries and that can benefit from the ecosystem of all three of these frameworks.
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Save and load models | TensorFlow Core
https://www.tensorflow.org/tutorials/keras/save_and_load
WebApr 3, 2024 · This guide uses tf.keras—a high-level API to build and train models in TensorFlow. The new, high-level .keras format used in this tutorial is recommended for saving Keras objects, as it provides robust, efficient name-based saving that is often easier to debug than low-level or legacy formats.
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Keras: Deep Learning for humans
https://keras.io/keras_3/
WebKeras 3 implements the full Keras API and makes it available with TensorFlow, JAX, and PyTorch — over a hundred layers, dozens of metrics, loss functions, optimizers, and callbacks, the Keras training and evaluation loops, and the Keras saving & …
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Training & evaluation with the built-in methods - Keras
https://keras.io/guides/training_with_built_in_methods/
WebMar 1, 2019 · You can use tf.data to train your Keras models regardless of the backend you're using – whether it's JAX, PyTorch, or TensorFlow. You can pass a Dataset instance directly to the methods fit() , evaluate() , and predict() :
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TensorFlow 2 Tutorial: Get Started in Deep Learning with tf.keras
https://machinelearningmastery.com/tensorflow-tutorial-deep-learning-with-tf-keras/
WebAug 2, 2022 · In this tutorial, you will discover a step-by-step guide to developing deep learning models in TensorFlow using the tf.keras API. After completing this tutorial, you will know: The difference between Keras and tf.keras and how to install and confirm TensorFlow is working
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keras · PyPI
https://pypi.org/project/keras/
WebApr 10, 2024 · Keras 3 is a multi-backend deep learning framework, with support for JAX, TensorFlow, and PyTorch. Effortlessly build and train models for computer vision, natural language processing, audio processing, timeseries forecasting, recommender systems, etc.
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GitHub - keras-team/keras: Deep Learning for humans
https://github.com/keras-team/keras
WebKeras 3 is a multi-backend deep learning framework, with support for JAX, TensorFlow, and PyTorch. Effortlessly build and train models for computer vision, natural language processing, audio processing, timeseries forecasting, recommender systems, etc.
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