Quick Intro to PyTorch with Examples: Tensor Operations

PyTorch (first released by Meta AI) is an open-source machine learning framework based on the Torch library. The framework combines the efficient and flexible GPU-accelerated backend libraries from Torch with an intuitive Python interface, allowing for easy prototyping. Torch is a library for scientific computing with wide support for machine learning algorithms and efficient GPU implementations thanks to C and CUDA. The fundamental work unit of PyTorch is the Tensor: a multi-dimensional matrix containing elements of a single data type, commonly used to store and manipulate the inputs and outputs of a model, as well as the model's parameters. Tensors are similar to NumPy's ndarray, except that tensors can run on GPUs for faster computing.