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Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications de Ian Pointer
Descripción - Reseña del editor Take the next steps toward mastering deep learning, the machine learning method that's transforming the world around us by the second. In this practical book, you'll get up to speed on key ideas using Facebook's 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 production Explore PyTorch use cases from several leading companies Learn how to apply transfer learning to images Apply cutting-edge NLP techniques using a model trained on Wikipedia Use PyTorch's torchaudio library to classify audio data with a convolutional-based model Debug PyTorch models using TensorBoard and flame graphs Deploy PyTorch applications in production in Docker containers and Kubernetes clusters running on Google Cloud Biografía del autor Currently Ian is the Director of Partner Engineering at a company called Kogentix that specializes in Machine Learning solutions (including Deep Learning techniques), with multiple Fortune 100 clients. Prior to that, he worked for many years at an early Big Data startup called Mammoth Data, cutting his teeth on Apache Hadoop and Apache Spark. He emigrated to the US from the UK in 2011 and became an American citizen in 2017.
Detalles del Libro
- Name: Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications
- Autor: Ian Pointer
- Categoria: Libros,Libros universitarios y de estudios superiores,Ciencias informáticas
- Tamaño del archivo: 15 MB
- Tipos de archivo: PDF Document
- Descargada: 196 times
- Idioma: Español
- Archivos de estado: AVAILABLE
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