by Jakub Konczyk | Released October 2018 | ISBN: 9781789138641

Journey into the world of deep learning using PyTorch. Recognize images, translate languages, and paint unique pictures.About This VideoDive into the world of deep learning with PyTorch by building interesting deep-learning projectsEnjoy your deep-learning journey and learn how to rapidly prototype your own neural networks in PyTorchThroughout the course, discover the joy of building neural networks in a Pythonic way in each projectIn DetailAre you ready to go on a journey into the world of deep learning? This course will be your guide through the joys and dangers of this new wave of machine learning. Why? Because, let's face it, getting started with deep learning is difficult. Tasks such as choosing between multiple frameworks, understanding APIs, and debugging code are hard. Is there an another way? Yes. Meet PyTorch. Like Python, PyTorch has a clean and simple API, which makes building neural networks faster and easier. It's also modular, and that makes debugging your code a breeze. This course will be one hell of an adventure into the world of deep learning!You'll start by using Convolutional Neural Networks (CNNs) to classify images; Recurrent Neural Networks (RNNs) to detect languages; and then translate them using Long-Term-Short Memory (LTSM). Finally, you'll channel your inner Picasso by using Deep Neural Network (DNN) to paint unique images.By the end of your adventure, you will be ready to use PyTorch proficiently in your real-world projects.The code bundle for this video course is available at - https://github.com/PacktPublishing/Deep-Learning-Adventures-with-PyTorchDownloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com. If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you. Show and hide more

1. Chapter 1 : First Stop: A Quick Introduction to PyTorch
   • The Course Overview 00:03:07
   • What Makes PyTorch Special? 00:02:12
   • Installing PyTorch 00:02:23
2. Chapter 2 : Sleeping Under the Stars: It's a Bird...It's a Plane...It’s a CNN?
   • Problem: Detect a Specific Type of Object in an Image 00:02:01
   • Quick Win: Using a Pretrained AlexNet Model for Beaver Detection 00:14:05
   • Getting and Preparing Image Data 00:09:41
   • Building, Training, and Testing Your Model 00:16:03
   • Using Your Model to Detect Beavers and What’s Next? 00:08:40
3. Chapter 3 : Going Abroad: Language Detection for Fun and Profit with RNN
   • Problem: Recognize the Language of a Specific Text 00:02:05
   • Understanding and Preparing Language Data 00:08:11
   • Building, Training, and Testing Your Model for Language Detection 00:18:31
   • Using Your Model to Detect Languages and What’s Next? 00:08:32
4. Chapter 4 : Making Friends: Lost in Translation with LSTM
   • Problem: Translate a Specific Text from One Language to Another 00:02:03
   • Understanding and Preparing Dataset for Language Translation 00:08:53
   • Building, Training, and Testing Your Models for Language Translation 00:16:28
   • Using Your Models for Language Translation 00:04:43
5. Chapter 5 : Getting Some Culture: Becoming a Deep Neural Picasso with DNN
   • Problem: Extract Key Style Features from One Image and Use It on Another One 00:02:10
   • Preparing Images for Style Transfer 00:05:12
   • Building and Training Style Transfer Model 00:16:29
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