Deep learning frameworks comparison
TensorFlow and PyTorch are the two leading deep learning frameworks. TensorFlow, developed by Google, is known for its production readiness, extensive ecosystem, and deployment capabilities. It uses a static computation graph approach (though eager execution is now default). PyTorch, developed by Facebook, is known for its Pythonic interface, dynamic computation graphs, and research-friendly design. Both frameworks support GPU acceleration, automatic differentiation, and have extensive libraries for computer vision, NLP, and reinforcement learning. TensorFlow's Keras API provides a high-level interface that simplifies model building, while PyTorch's torch.nn module offers similar functionality. The choice between them often depends on use case: TensorFlow for production deployment, PyTorch for research and experimentation. However, both frameworks are converging in features and either can be used for most deep learning tasks.