What is TensorFlow 0?
TensorFlow 2.0 is an updated version of TensorFlow that has been designed with a focus on simple execution, ease of use, and developer’s productivity. TensorFlow 2.0 makes the development of data science and machine learning applications even easier. With updated features like tight integration of Keras, default Eager execution, and Pythonic function execution, there have been considerable and successful efforts to make the experience of developing applications more familiar for Python developers.
The TensorFlow team has also invested heavily in low-level API this time. All the ops that are used internally are now exported and inheritable interfaces for concepts such as variables and checkpoints are provided. So, as you build onto the internals of TensorFlow, you won’t have to rebuild TensorFlow.
Tensorflow 1.xvs. Tensorflow 2.x: What’s the Difference?
TensorFlow is an end-to-end open-source machine learning platform that contains comprehensive tools, libraries and community resources. It is meant for developers, data scientists and researchers to build and deploy applications powered by machine learning. TensorFlow was essentially built to scale, developed by Google Brain team, TensorFlow accelerates ML and deep neural network research. It can run on multiple CPUs or GPUs and mobile operating systems. Also, it has several wrappers in languages like Python, C++, or Java.