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The Model class. [source] Model class. keras.Model() A model grouping layers into an object with training/inference features. There are three ways to instantiate a Model: With the "Functional API" You start from Input, you chain layer calls to specify the model's forward pass, and finally, you create your model from inputs and outputs:
May 2, 2024 · Keras is an open-source deep-learning framework that gained attention due to its user-friendly interface. Keras offers ease of use, flexibility, and the ability to run seamlessly on top of TensorFlow. In this article, we are going to provide a comprehensive overview of Keras.
Mar 23, 2024 · Most models are made of layers. Layers are functions with a known mathematical structure that can be reused and have trainable variables. In TensorFlow, most high-level implementations of layers and models, such as Keras or Sonnet, are built on the same foundational class: tf.Module. Building Modules.
Jun 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.
A model grouping layers into an object with training/inference features. Arguments. inputs: The input (s) of the model: a keras.Input object or a combination of keras.Input objects in a dict, list or tuple.
Apr 30, 2021 · 6 Hyperparameter Tuning. 7 Summary. What is Keras. Keras is a high-level deep learning python library for developing neural network models. Keras is a high-level API wrapper. It can run on top of the Tensorflow, CTNK, and Theano library. Keras is developed for the easy and fast development of neural network models. Benefits and Limitations.
There are three ways to create Keras models: The Sequential model, which is very straightforward (a simple list of layers), but is limited to single-input, single-output stacks of layers (as the name gives away). The Functional API, which is an easy-to-use, fully-featured API that supports arbitrary model architectures.
