Comet.ml vs PyTorch: What are the differences?
Comet.ml: Track, compare and collaborate on Machine Learning experiments. Comet.ml allows data science teams and individuals to automagically track their datasets, code changes, experimentation history and production models creating efficiency, transparency, and reproducibility; PyTorch: 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.
Comet.ml and PyTorch can be categorized as "Machine Learning" tools.
PyTorch is an open source tool with 29.6K GitHub stars and 7.18K GitHub forks. Here's a link to PyTorch's open source repository on GitHub.
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!!