Learn PyTorch from Pluralsight

Pluralsight offers you 9 courses, to learn PyTorch now!

Pluralsight, is an American publicly held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 6,500 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.

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Deploying PyTorch Models in Production: PyTorch Playbook

This course covers the important aspects of performing distributed training of PyTorch models^ using the multiprocessing^ data-parallel^ and distributed data-parallel approaches. It also discusses which you can host PyTorch models for prediction.

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Building Your First PyTorch Solution

This course covers the important practical aspects of installing PyTorch from scratch on a variety of different platforms and getting going with classification and regression models.

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Foundations of PyTorch

This course covers many aspects of building deep learning models in PyTorch^ including neurons and neural networks^ and how PyTorch uses differential calculus to train such models and create dynamic computation graphs in deep learning.

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Image Classification with PyTorch

This course covers the parts of building enterprise-grade image classification systems like image pre-processing^ picking between CNNs and DNNs^ calculating output dimensions of CNNs^ and leveraging pre-trained models using PyTorch transfer learning.

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Natural Language Processing with PyTorch

This course covers the use of advanced neural network constructs and architectures^ such as recurrent neural networks^ word embeddings^ and bidirectional RNNs^ to solve complex word and language modeling problems using PyTorch.

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Using PyTorch in the Cloud: PyTorch Playbook

This course covers the important aspects of using PyTorch on Amazon Web Services (AWS)^ Microsoft Azure^ and the Google Cloud Platform (GCP)^ including the use of cloud-hosted notebooks^ deep learning VM instances with GPU support^ and PyTorch estimators.

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Expediting Deep Learning with Transfer Learning: PyTorch Playbook

This course covers the important design choices that a data professional must make while leveraging pre-trained models using Transfer Learning. It also covers the implementation aspects of different Transfer Learning approaches in PyTorch.

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Style Transfer with PyTorch

This course covers the important aspects of neural style transfer^ a technique for transforming images^ and discusses Generative Adversarial Networks in order to efficiently create realistic images and videos.

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Getting Started with Tensorflow 2.0

This course focuses on introducing the TensorFlow 2.0 framework - exploring the features and functionality that it offers for building and training neural networks. This course discusses how TensorFlow 2.0 differs from TensorFlow 1.x and how the use of the …

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