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TensorFlow 2.0 is the latest version of Google's open-source machine learning framework. It was released in 2019 and comes with significant improvements and new features compared to its predecessor, TensorFlow 1.x.

One of the major changes in TensorFlow 2.0 is that it now uses eager execution by default, which makes it easier to debug and develop models. Additionally, it has a simpler API and a more streamlined workflow, allowing users to build and train models with less code.

Another key feature of TensorFlow 2.0 is its support for Keras, a high-level neural network API that provides an easy-to-use interface for building and training deep learning models. Keras is now integrated into TensorFlow, which means that users can seamlessly switch between the two libraries.

TensorFlow 2.0 also includes a number of performance improvements, such as faster model training and improved GPU utilization. It also includes support for new hardware, such as the TPU (Tensor Processing Unit), which is designed to accelerate machine learning workloads.

Overall, TensorFlow 2.0 is a major update to the popular machine learning framework, making it more user-friendly, efficient, and powerful. It is widely used in industry and academia for a variety of applications, including computer vision, natural language processing, and speech recognition.