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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.
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.
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.
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.
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.
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?
Mar 9, 2023 · Keras is a high-level, user-friendly API used for building and training neural networks. It is an open-source library built in Python that runs on top of TensorFlow. It was developed to enable fast experimentation and iteration, and it lowers the barrier to entry for working with deep learning.
