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May 2, 2024 · Keras is a high-level, user-friendly API used for building and training neural networks. It is designed to be user-friendly, modular, and easy to extend. Keras allows you to build, train, and deploy deep learning models with minimal code.
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?
Jun 8, 2023 · With Keras, you have full access to the scalability and cross-platform capabilities of TensorFlow. You can run Keras on a TPU Pod or large clusters of GPUs, and you can export Keras models to run in the browser or on mobile devices. You can also serve Keras models via a web API.
The purpose of Keras is to give an unfair advantage to any developer looking to ship Machine Learning-powered apps. 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.
Keras is an open-source library that provides a Python interface for artificial neural networks. Keras was first independent software, then integrated into the TensorFlow library, and later supporting more.
Jun 17, 2022 · Keras is a powerful and easy-to-use free open source Python library for developing and evaluating deep learning models. It is part of the TensorFlow library and allows you to define and train neural network models in just a few lines of code.
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.
Dec 10, 2019 · One of the most powerful and easy-to-use Python libraries for developing and evaluating deep learning models is Keras; It wraps the efficient numerical computation libraries Theano and TensorFlow. The advantage of this is mainly that you can get started with neural networks in an easy and fun way.
Sep 13, 2019 · What is Keras? Keras is a minimalist Python library for deep learning that can run on top of Theano or TensorFlow. It was developed to make implementing deep learning models as fast and easy as possible for research and development. It runs on Python 2.7 or 3.5 and can seamlessly execute on GPUs and CPUs given the underlying frameworks.
Keras is an open-source, high-level neural networks API written in Python. It was developed with a focus on enabling fast experimentation and prototyping in the field of deep learning. Keras provides a user-friendly and intuitive interface, making it accessible to both beginners and experienced machine learning practitioners.
