Intro to KERAS 3 (KERAS core) for PyTorch & JAX

Keras is a popular open-source deep learning library written in Python. It is known for its user-friendly interface, modularity, and ease of use. Keras 3, also known as Keras core, is the latest version of the library and offers several improvements and new features.

What is PyTorch?

PyTorch is another popular machine learning library that is widely used for deep learning tasks. It is known for its dynamic computation graph and flexibility. With the release of Keras 3, it is now possible to use Keras with PyTorch, allowing users to take advantage of the strengths of both libraries.

What is JAX?

JAX is an open-source library from Google that provides high-performance machine learning and numerical computing. It is particularly well-suited for complex probabilistic models and deep learning. Keras 3 also offers compatibility with JAX, making it easier for users to leverage the benefits of both libraries.

New Features in Keras 3

Keras 3 introduces several new features and improvements, including:

• Support for PyTorch backend
• Integration with JAX for high-performance computing
• Improved performance and stability
• Updated documentation and examples

Getting Started with Keras 3

To get started with Keras 3, you can visit the official Keras website and download the latest version of the library. The documentation provides detailed instructions on how to use Keras with PyTorch and JAX, as well as examples to help you get started with your deep learning projects.

Conclusion

Keras 3 is an exciting new release that offers compatibility with PyTorch and JAX, two of the most popular machine learning libraries. By leveraging the strengths of these libraries, users can take advantage of the latest advancements in deep learning and high-performance computing. Whether you are a beginner or an experienced deep learning practitioner, Keras 3 provides the tools you need to build and train your machine learning models.