What are the main characteristics of TensorFlow?

The key features of TensorFlow are:

1. Flexibility: TensorFlow has the capability to run on different hardware devices such as CPU, GPU, and TPU, supporting distributed computing and allowing parallel training and inference of models across multiple devices.
2. High performance: TensorFlow uses a computational graph to define and optimize the computing process, enabling automatic optimization and parallelization of the graph to improve the speed of model training and inference.
3. Robust scalability: TensorFlow offers a wide range of APIs and tools that make it easy to create various types of neural network models. Custom operations and loss functions can also be easily integrated into the models.
4. Cross-platform support: TensorFlow is compatible with various operating systems such as Windows, Linux, and macOS, as well as mobile devices and embedded systems.
5. Community support: TensorFlow has a large user community and active developer community, where users can share and exchange the latest research results and application cases, providing abundant resources and support.