PyTorch vs Theano: What are the differences?
Developers describe PyTorch as "A deep learning framework that puts Python first". PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc. On the other hand, Theano is detailed as "Define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently". Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray). Using Theano it is possible to attain speeds rivaling hand-crafted C impleme.
PyTorch and Theano belong to "Machine Learning Tools" category of the tech stack.
PyTorch and Theano are both open source tools. PyTorch with 29.6K GitHub stars and 7.18K forks on GitHub appears to be more popular than Theano with 8.83K GitHub stars and 2.49K GitHub forks.
I have just started learning some basic machine learning concepts. So which of the following frameworks is better to use: Keras / TensorFlow/PyTorch. I have prior knowledge in python(and even pandas), java, js and C. It would be nice if something could point out the advantages of one over the other especially in terms of resources, documentation and flexibility. Also, could someone tell me where to find the right resources or tutorials for the above frameworks? Thanks in advance, hope you are doing well!!