Model Complexity: For highly complex models that require intense computation, TensorFlow’s graph-based approach can be beneficial.

Google has released a new open source library designed to enable developers to more easily create graph neural networks with TensorFlow.

While it is improving in production environments, TensorFlow remains the preferred choice for large-scale deployments due to its static graph optimisations and enterprise-level support.

TensorFlow works seamlessly on Linux, allowing developers to leverage NVIDIA CUDA and TensorRT for faster computations. PyTorch PyTorch, developed by Facebook's AI Research Lab, is another popular ...