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PyTorch vs Streamlit: 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, Streamlit is detailed as "A Python app framework built specifically for Machine Learning and Data Science teams". It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.
PyTorch and Streamlit belong to "Machine Learning Tools" category of the tech stack.
PyTorch and Streamlit are both open source tools. PyTorch with 32.4K GitHub stars and 8K forks on GitHub appears to be more popular than Streamlit with 2.73K GitHub stars and 184 GitHub forks.
Pros of PyTorch
- Easy to use15
- Developer Friendly11
- Easy to debug10
- Sometimes faster than TensorFlow7
Pros of Streamlit
- Fast development11
- Fast development and apprenticeship1
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Cons of PyTorch
- Lots of code3
- It eats poop1
Cons of Streamlit
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What is PyTorch?
What is Streamlit?
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What tools integrate with PyTorch?
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