PyTorch Tutorial 1: Introduction to Tensors
Google colab: https://colab.research.google.com/
PyTorch: https://www.tensorflow.org/install/pip
Github Tutorial Repo: https://github.com/viibrem/yt_tutorials
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PyTorch is an open-source machine learning library developed by Facebook's AI research team, and it is widely used by researchers and practitioners worldwide due to its simplicity, flexibility, and powerful features.
In this tutorial, we will start by exploring what PyTorch is and its key features that make it a popular choice for machine learning tasks. Then, we will dive into the concept of tensors, which are the primary data structure used in PyTorch to represent and manipulate data.
We will discuss the different types of tensors and their properties, including dimensions, shape, and data type. We will also demonstrate how to create tensors using PyTorch and perform basic operations on them, such as addition, multiplication, and matrix multiplication.
Throughout the tutorial, we will provide code examples to illustrate how PyTorch tensors and operations work in practice. By the end of this tutorial, you will have a solid understanding of PyTorch and be able to start using it in your machine learning projects.
So, whether you're a beginner or an experienced practitioner, join us and learn how to use PyTorch to build powerful machine-learning models.
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