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PyTorch Deep Learning in 7 Days
PyTorch Deep Learning in 7 Days

PyTorch Deep Learning in 7 Days: Boost your career in one week with the cutting-edge field of Deep Learning with PyTorch

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Profile Icon Will Ballard
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R$768.99
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3 (1 Ratings)
Video Mar 2019 2hrs 9mins 1st Edition
Video
R$768.99
Subscription
Free Trial
Renews at R$50p/m
Arrow left icon
Profile Icon Will Ballard
Arrow right icon
R$768.99
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3 (1 Ratings)
Video Mar 2019 2hrs 9mins 1st Edition
Video
R$768.99
Subscription
Free Trial
Renews at R$50p/m
Video
R$768.99
Subscription
Free Trial
Renews at R$50p/m

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Key benefits

  • A systematic guide on Deep Learning to help you build smart applications
  • Cover core concepts and architectures of Deep Learning systems without getting bogged down in mathematical notation
  • Solve Machine Learning problems by applying Deep Learning architectures

Description

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.

Who is this book for?

This course is for software development professionals and machine learning enthusiasts, who have heard the hype of Deep Learning and want to learn it to stay relevant in their field. Basic knowledge of machine learning concepts and Python programming is required.

What you will learn

  • Get comfortable with most commonly used PyTorch concepts, modules and API including Tensor operations, data representations, and manipulation
  • Work with Deep Learning models and architectures including layers, activations, loss functions, gradients, chain rule, forward and backward passes, and optimizers
  • Apply Deep Learning architectures to solve Machine Learning problems for Structured Datasets, Computer Vision, and Natural Language Processing
  • Utilize the concept of Transfer Learning by using pre-trained Deep Learning models to your own problems
  • Implement state of the art in Natural Language Processing to solve real-world problems such as sentiment analysis
  • Implement a simple Generative Adversarial Network to generate fancy images after training on a large image dataset

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 30, 2019
Length: 2hrs 9mins
Edition : 1st
Language : English
ISBN-13 : 9781789135367
Category :
Languages :
Concepts :
Tools :

What do you get with a video?

Product feature icon Download this video in MP4 format
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want

Product Details

Publication date : Mar 30, 2019
Length: 2hrs 9mins
Edition : 1st
Language : English
ISBN-13 : 9781789135367
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Table of Contents

7 Chapters
Getting started with PyTorch Chevron down icon Chevron up icon
Building a Neural Network Chevron down icon Chevron up icon
Regression and Classification Chevron down icon Chevron up icon
Implementing Convolutional Neural Networks Chevron down icon Chevron up icon
Implementing Transfer Learning Chevron down icon Chevron up icon
LSTM and Embedding for Natural Language Models Chevron down icon Chevron up icon
Deep Convolutional Generative Adversarial Networks Chevron down icon Chevron up icon

Customer reviews

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N/A Jan 31, 2020
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Cart does not reliably credit for advertised discount. Once a purchase is made, website fails to provide adequate means to for finding purchased content. The bootstrap-javascript front end makes display dynamic and causes order to be inconsistent. Very challenging to track learning progress. Many titles add little info.
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