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PyTorch Deep Learning Hands-On

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Learn

Use PyTorch to build:

  • Simple Neural Networks – build neural networks the PyTorch way, with high-level functions, optimizers, and more
  • Convolutional Neural Networks – create advanced computer vision systems
  • Recurrent Neural Networks – work with sequential data such as natural language and audio
  • Generative Adversarial Networks – create new content with models including SimpleGAN and CycleGAN
  • Reinforcement Learning – develop systems that can solve complex problems such as driving or game playing
  • Deep Learning workflows – move effectively from ideation to production with proper deep learning workflow using PyTorch and its utility packages
  • Production-ready models – package your models for high-performance production environments
About

PyTorch is a new, lightweight, and Python-first tool for deep learning. Built by Facebook to offer flexibility and speed, it has quickly become the preferred tool for deep learning experts. PyTorch helps you release deep learning models faster than ever before.

PyTorch Deep Learning Hands-On shows how to implement every major deep learning architecture in PyTorch. Starting with simple neural networks, it covers PyTorch for computer vision (CNN), natural language processing (RNN), GANs, and reinforcement learning. You will also build deep learning workflows with the PyTorch framework, migrate models built in Python to highly efficient TorchScript, and deploy to production using the most sophisticated available tools.

Each chapter focuses on a different area of deep learning. Chapters start with a refresher on the core principles, before sharing the code you need to implement them in PyTorch.

If you want to become a deep learning expert this book is for you.

Features
  • Understand the internals and principles of PyTorch
  • Implement key deep learning methods in PyTorch: CNNs, GANs, RNNs, reinforcement learning, and more
  • Build deep learning workflows and take deep learning models from prototyping to production
Page Count 250
Course Length 7 hours 30 minutes
ISBN 9781788834131
Date Of Publication 29 Apr 2019

Authors

Sherin Thomas

Sherin Thomas started his career as an information security expert and shifted his focus to deep learning-based security systems. He has helped several companies across the globe to set up their AI pipelines and worked recently for CoWrks, a fast-growing start-up based out of Bengaluru. Sherin is working on several open source projects including PyTorch, RedisAI, and many more, and is leading the development of TuringNetwork.ai. Currently, he is focusing on building the deep learning infrastructure for [tensor]werk, an Orobix spin-off company.

Sudhanshu Passi

Sudhanshu Passi is a technologist employed at CoWrks. Among other things, he has been the driving force behind everything related to machine learning at CoWrks. His expertise in simplifying complex concepts makes his work an ideal read for beginners and experts alike. This can be verified by his many blogs and this debut book publication. In his spare time, he can be found at his local swimming pool computing gradient descent underwater.