TensorFlow and PyTorch, two popular deep learning frameworks, differ in their approach to computational graphs. TensorFlow uses a static computational graph, where the graph structure is defined before the actual computation occurs. In contrast, PyTorch employs a dynamic
Consider using the TensorFlow library for deep learning and neural network development in Python. TensorFlow offers a comprehensive ecosystem for building and deploying machine learning models, with support for both CPU and GPU acceleration.