PyTorch: An Introduction Guide to Pytorch Deep Learning With Python for Beginners, 2019 Edition.

by Jim Smith

PyTorch Deep LearningPyTorch is defined as an open source machine learning library for Python. It is used for applications such as natural language processing. It is initially developed by Facebook artificial-intelligence research group, and Uber’s Pyro software for probabilistic programming which is built on it. Originally, PyTorch was developed by Hugh Perkins as a Python wrapper for the LusJIT based on Torch framework. There are two PyTorch variants. PyTorch redesigns and implements Torch in Python while sharing the same core C libraries for the backend code. PyTorch developers tuned this back-end code to run Python efficiently. They also kept the GPU based hardware acceleration as well as the extensibility features that made Lua-based Torch. This book has been prepared for python developers who focus on research and development with machine learning algorithms along with natural language processing system. The aim of this tutorial is to completely describe all concepts of PyTorch and realworld examples of the same. What you will IntroductionInstallationNeural Network BasicsUniversal Workflow of Machine LearningMachine Learning vs. Deep LearningImplementing First Neural NetworkNeural Networks to Functional BlocksTerminologiesLoading DataLinear RegressionConvolutional Neural NetworkRecurrent Neural NetworkDatasetsIntroduction to ConventsTraining a Convent from ScratchFeature Extraction in ConventsVisualization of ConventsProcessing with ConventsWord EmbeddingRecursive Neural Networks

69 pages, Kindle Edition

Published September 2, 2019

About the author

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Jim Smith, the laziest (yet still professional) teacher in town, is a head of school, education consultant, Independent Thinking Associate, speaker and bestselling author.