Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications - KaedenHanson/KaedenHansonbook GitHub Wiki

 

Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications



Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications






Take the next steps toward mastering deep learning, the machine learning method that8217s transforming the world around us by the second. In this practical book, you8217ll get up to speed on key ideas using Facebook8217s open source PyTorch framework and gain the latest skills you need to create your very own neural networks.Ian Pointer shows you how to set up PyTorch on a cloud-based environment, then walks you through the creation of neural architectures that facilitate operations on images, sound, text,and more through deep dives into each element. He also covers the critical concepts of applying transfer learning to images, debugging models, and PyTorch in production.Learn how to deploy deep learning models to productionExplore PyTorch use cases from several leading companiesLearn how to apply transfer learning to imagesApply cutting-edge NLP techniques using a model trained on WikipediaUse PyTorch8217s torchaudio library to classify audio data with a convolutional-based modelDebug PyTorch models using TensorBoard and flame graphsDeploy PyTorch applications in production in Docker containers and Kubernetes clusters running on Google Cloud

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