What are the main differences between TensorFlow and PyTorch?
TensorFlow is more focused on production and deployment, while PyTorch is favored for research and flexibility.
Is TensorFlow better for large-scale projects?
Yes, TensorFlow offers better support for distributed computing and scalability, making it ideal for large-scale projects.
How does TensorFlow compare to Keras?
Keras is actually a high-level API built on top of TensorFlow, making it easier to build and train models.
What about other frameworks like MXNet or Caffe?
MXNet is known for its efficiency and scalability, while Caffe is optimized for image processing tasks.
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