What are the key advantages of TensorFlow over Caffe in machine learning?
The question is about TensorFlow .
TensorFlow is more flexible and scalable than Caffe. While Caffe is focused on images, TensorFlow supports many tasks - such as NLP, reinforcement learning, and generative models - thanks to its open architecture. TensorFlow also offers tools for mobile (TensorFlow Lite), visualisation (TensorBoard), and deployment (TensorFlow Serving), along with a strong community and documentation. Another big advantage is that TensorFlow lets you train on multiple GPUs or TPUs, making it better suited to large, complex machine-learning tasks.
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