PyTorch Beginner Tutorial Tensors

PyTorch Beginner Tutorial - Tensors

Introduction to Pytorch

PyTorch is a high-level framework for efficiently creating and training deep learning architectures such as Feed-Forward Neural Networks (FFNN), RNN, and CNN. It is an incredibly useful tool because it allows you to perform nifty natural language processing (NLP) and computer vision (CV) tasks. You can use PyTorch to create models that perform NLP tasks such as sentiment analysis, translation, summarization, and even text generation (smart speech bots). Some CV tasks that you can perform using PyTorch are object classification/detection, semantic segmentation, and real-time image processing. Of course, PyTorch can be used for other applications including audio files, medical files, and time-series forecasting.

Contents:

• Tensor Creation and Attributes
• Tensor Operations
• Using right Hardware

Tensor Creation and Attributes

In this tutorial, we explain the building block of PyTorch operations: Tensors. Tensors are essentially PyTorch's implementation of arrays. Since machine learning is moslty matrix manipulation, you will need to be familiar with tensor operations

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