TensorFlow 2 is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks.
TensorFlow 2 was released in September 2019 as a major update to the original TensorFlow library. It includes a number of new features and improvements, including:
- Eager execution: Eager execution is a new mode of execution in TensorFlow 2 that allows you to run TensorFlow code without having to build a computational graph first. This makes it easier to debug and develop TensorFlow models.
- Keras: Keras is a high-level API for building deep learning models in TensorFlow. Keras was originally a separate project, but it was integrated into TensorFlow 2. This makes it easier to build and deploy deep learning models in TensorFlow.
- Improved documentation: The documentation for TensorFlow 2 has been significantly improved over the documentation for the original TensorFlow library. This makes it easier to learn how to use TensorFlow 2.
Benefits of using TensorFlow 2:
- Easier to learn: TensorFlow 2 is easier to learn than the original TensorFlow library. The documentation is better, and the API is more intuitive.
- More efficient: TensorFlow 2 is more efficient than the original TensorFlow library. This is because it uses a new execution engine that is optimized for speed.
- More powerful: TensorFlow 2 is more powerful than the original TensorFlow library. This is because it includes new features and improvements, such as eager execution and Keras.
TensorFlow 2 is a major improvement over the original TensorFlow library. It is easier to use, more efficient, and more powerful.
