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Training Machine Learning Models Using TensorFlow or PyTorch

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AI and machine learning are very hot topics these days. These are only some of the applications that cannot exist without machine learning. But how can machines learn? I will show you how the magic works in this article, but I won't talk about neural networks! I will show you what is in the deepest deep of machine learning. One of the best presentations about machine learning is Fei Fei Li's TED talk.


PyTorch for Deep Learning: A Quick Guide for Starters

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Since there are multiple optimization schemes to choose from, we just need to choose one for our problem and rest the underlying PyTorch library does the magic for us.


Introduction to PyTorch

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Recently, Microsoft and PyTorch announced a "PyTorch Fundamentals" tutorial, which you can find on Microsoft's site and on PyTorch's site. The code in this post is based on the code appearing in that tutorial, and forms the foundation for a series of other posts, where I'll explore other machine learning frameworks and show integration with Azure ML. In this post, I'll explain how you can create a basic neural network in PyTorch, using the Fashion MNIST dataset as a data source. The neural network we'll build takes as input images of clothing, and classifies them according to their contents, such as "Shirt," "Coat," or "Dress." I'll assume that you have a basic conceptual understanding of neural networks, and that you're comfortable with Python, but I assume no knowledge of PyTorch. Let's start by getting familiar with the data we'll be using, the Fashion MNIST dataset.


PyTorch tutorial: a quick guide for new learners

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Python is well-established as the go-to language for data science and machine learning, partially thanks to the open-source ML library PyTorch. As its popularity grows, more and more companies are moving from TensorFlow to PyTorch, making now the best time to get started with PyTorch. Today, we'll help understand what makes PyTorch so popular, some basics of using PyTorch, and help you make your first computational models. PyTorch is an open-source machine learning Python library used for deep learning implementations like computer vision (using TorchVision) and natural language processing. It was developed by Facebook's AI research lab (FAIR) in 2016 and has since been adopted across the fields of data science and ML.


Learn PyTorch in 10 minutes

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PyTorch is an open source Machine Learning library based on the Torch library, used for applications such as computer vision and natural language processing. PyTorch is an open source Machine Learning library based on the Torch library, used for applications such as computer vision and natural language processing. This tutorial introduces the fundamental concepts of PyTorch through self-contained examples. We will use a fully-connected ReLU network as our running example. The network will have a single hidden layer, and will be trained with gradient descent to fit random data by minimizing the Euclidean distance between the network output and the true output.