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Book Overview & Buying
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Table Of Contents
PyTorch Deep Learning in 7 Days
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PyTorch Deep Learning in 7 Days
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Overview of this book
PyTorch is Facebook’s latest Python-based framework for Deep Learning. It has the ability to create dynamic Neural Networks on CPUs and GPUs, both with a significantly less code compared to other competing frameworks. PyTorch has a unique interface that makes it as easy to learn as NumPy.
This 7-day course is for those who are in a hurry to get started with PyTorch. You will be introduced to the most commonly used Deep Learning models, techniques, and algorithms through PyTorch code. This course is an attempt to break the myth that Deep Learning is complicated and show you that with the right choice of tools combined with a simple and intuitive explanation of core concepts, Deep Learning is as accessible as any other application development technologies out there. It’s a journey from diving deep into the fundamentals to getting acquainted with the advance concepts such as Transfer Learning, Natural Language Processing and implementation of Generative Adversarial Networks.
By the end of the course, you will be able to build Deep Learning applications with PyTorch.
All the code and supporting files for this course are available on GitHub at: https://github.com/PacktPublishing/PyTorch-Deep-Learning-in-7-Days
This course uses Python 3.7 and PyTorch 1.1 while not the latest version available, it provides relevant and informative content for legacy users of PyTorch.
Table of Contents (7 chapters)
Getting started with PyTorch
Building a Neural Network
Regression and Classification
Implementing Convolutional Neural Networks
Implementing Transfer Learning
LSTM and Embedding for Natural Language Models
Deep Convolutional Generative Adversarial Networks
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