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What is PyTorch?
PyTorch is an open-source deep learning framework built on Torch. Its core is implemented in C++, and it emphasizes a Python-first design, so using it is similar to writing standard Python projects and it integrates well with Python libraries. For beginners, PyTorch offers an intuitive architecture and concise syntax; its lightweight design also enables relatively fast model training.
What is TensorFlow?
TensorFlow has been one of the popular frameworks for building deep learning models since it became open source. Its popularity stems partly from being free and from being relatively easy to get started with; even machine learning beginners can use the library's built-in functions and datasets instead of building everything from scratch.
Key differences between PyTorch and TensorFlow
Both PyTorch and TensorFlow are suitable entry points into artificial intelligence, but they differ in several ways. PyTorch is generally easier to use and more flexible; users with a Python background often adopt it more easily. TensorFlow offers a more complete ecosystem of models and tutorials, with many modules packaged and optimized for production use.
PyTorch's dynamic graph design makes it convenient for researchers to modify and experiment. TensorFlow often has advantages in computational efficiency, and because it was developed earlier, many applications and industry deployments are based on TensorFlow. In industrial practice, existing widespread use tends to favor TensorFlow unless a substantial shift occurs.
