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This article will explain in detail what are the features of TensorFlow 2.0. the content of the article is of high quality, so the editor will share it for you as a reference. I hope you will have some understanding of the relevant knowledge after reading this article.

Here are some new features of 2.0.

Functional API

Of course, the sequential model is a simple layer stack and cannot represent any model. You can build more advanced models using Functional API, which allows you to define complex topologies, including multi-input and multi-output models, models with shared layers, and models with remaining connections.

High-order API

-Keras, the TensorFlow high-level API used to build and train deep learning models. -Eager Execution, an API that writes TensorFlow code in a command manner, just like using NumPy.

Sequential API

If you are a student studying ML, we recommend that you start using tf.keras Sequential API. It is intuitive, concise and suitable for 95% of ML problems in practice. With this API, you can write your first neural network in about 10 lines of code.

How to install tf.keraspip install tensorflow about TensorFlow 2.0 features is shared here, I hope the above content can be of some help to you, can learn more knowledge. If you think the article is good, you can share it for more people to see.

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