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

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

Jim Smith
2.8/5 ( ratings)
Read Download
PyTorch Deep Learning

PyTorch 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 learn:

Introduction Installation Neural Network Basics Universal Workflow of Machine Learning Machine Learning vs. Deep Learning Implementing First Neural Network Neural Networks to Functional Blocks Terminologies Loading Data Linear Regression Convolutional Neural Network Recurrent Neural Network Datasets Introduction to Convents Training a Convent from Scratch Feature Extraction in Convents Visualization of Convents Processing with Convents Word Embedding Recursive Neural Networks
Pages
69
Format
Kindle Edition
Release
September 02, 2019

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

Jim Smith
2.8/5 ( ratings)
Read Download
PyTorch Deep Learning

PyTorch 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 learn:

Introduction Installation Neural Network Basics Universal Workflow of Machine Learning Machine Learning vs. Deep Learning Implementing First Neural Network Neural Networks to Functional Blocks Terminologies Loading Data Linear Regression Convolutional Neural Network Recurrent Neural Network Datasets Introduction to Convents Training a Convent from Scratch Feature Extraction in Convents Visualization of Convents Processing with Convents Word Embedding Recursive Neural Networks
Pages
69
Format
Kindle Edition
Release
September 02, 2019

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