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Deep Learning with PyTorch (Video)
Deep Learning with PyTorch (Video)

Deep Learning with PyTorch (Video): Start your deep learning journey with PyTorch

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Profile Icon Anand Saha
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$19.99 per month
Video Apr 2018 4hrs 42mins 1st Edition
Video
$137.99
Subscription
Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Anand Saha
Arrow right icon
$19.99 per month
Video Apr 2018 4hrs 42mins 1st Edition
Video
$137.99
Subscription
Free Trial
Renews at $19.99p/m
Video
$137.99
Subscription
Free Trial
Renews at $19.99p/m

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Key benefits

  • Explore PyTorch and the impact it has made on Deep Learning
  • Design and implement powerful neural networks to solve some impressive problems in a step-by-step manner
  • Follow the examples to solve similar use cases outside this course

Description

This video course will get you up-and-running with one of the most cutting-edge deep learning libraries: PyTorch. Written in Python, PyTorch is grabbing the attention of all data science professionals due to its ease of use over other libraries and its use of dynamic computation graphs. In this course, you will learn how to accomplish useful tasks using Convolutional Neural Networks to process spatial data such as images and using Recurrent Neural Networks to process sequential data such as texts. You will explore how you can make use of unlabeled data using Auto Encoders. You will also be training a neural network to learn how to balance a pole all by itself, using Reinforcement Learning. Throughout this journey, you will implement various mechanisms of the PyTorch framework to do these tasks. By the end of the video course, you will have developed a good understanding of, and feeling for, the algorithms and techniques used. You’ll have a good knowledge of how PyTorch works and how you can use it in to solve your daily machine learning problems. All the code and supporting files for this course are available on GitHub at https://github.com/PacktPublishing/Deep-learning-with-PyTorch-video. This course uses Python 3.6, and PyTorch 0.3, while not the latest version available, it provides relevant and informative content for legacy users of Python, and PyTorch.

Who is this book for?

This course is for Python programmers who have some knowledge of machine learning and want to build Deep Learning systems with PyTorch. Python programming knowledge and minimal math skills (matrix/vector manipulation, simple probabilities) is assumed.

What you will learn

  • Understand PyTorch and Deep Learning concepts
  • Build your neural network using Deep Learning techniques in PyTorch.
  • Perform basic operations on your dataset using tensors and variables
  • Build artificial neural networks in Python with GPU acceleration
  • See how CNN works in PyTorch with a simple computer vision example
  • Train your RNN model from scratch for text generation
  • Use Auto Encoders in PyTorch to remove noise from images
  • Perform reinforcement learning to solve OpenAI's Cartpole task
  • Extend your knowledge of Deep Learning by using PyTorch to solve your own machine learning problems

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Apr 30, 2018
Length: 4hrs 42mins
Edition : 1st
Language : English
ISBN-13 : 9781788475266
Category :
Languages :
Concepts :
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What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Product Details

Publication date : Apr 30, 2018
Length: 4hrs 42mins
Edition : 1st
Language : English
ISBN-13 : 9781788475266
Category :
Languages :
Concepts :
Tools :

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Table of Contents

6 Chapters
Getting Started With PyTorch Chevron down icon Chevron up icon
Training Your First Neural Network Chevron down icon Chevron up icon
Computer Vision – CNN for Digits Recognition Chevron down icon Chevron up icon
Sequence Models – RNN for Text Generation Chevron down icon Chevron up icon
Autoencoder - Denoising Images Chevron down icon Chevron up icon
Reinforcement Learning – Balance Cartpole Using DQN Chevron down icon Chevron up icon
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