logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Programming Pytorch For Deep Learning Ian Pointer

  • SKU: BELL-49847756
Programming Pytorch For Deep Learning Ian Pointer
$ 31.00 $ 45.00 (-31%)

5.0

88 reviews

Programming Pytorch For Deep Learning Ian Pointer instant download after payment.

Publisher: O'Reilly Media
File Extension: PDF
File size: 6.35 MB
Pages: 220
Author: Ian Pointer
Language: English
Year: 2019

Product desciption

Programming Pytorch For Deep Learning Ian Pointer by Ian Pointer instant download after payment.

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

Related Products