Hlustaðu og lestu

Stígðu inn í heim af óteljandi sögum

  • Lestu og hlustaðu eins mikið og þú vilt
  • Þúsundir titla
  • Getur sagt upp hvenær sem er
  • Engin skuldbinding
Prófa frítt
is Device Banner Block 894x1036
Cover for PyTorch Deep Learning Hands-On: Build CNNs, RNNs, GANs, reinforcement learning, and more, quickly and easily

PyTorch Deep Learning Hands-On: Build CNNs, RNNs, GANs, reinforcement learning, and more, quickly and easily

Tungumál
enska
Snið
Bókaflokkur

Óskáldað efni

Hands-on projects cover all the key deep learning methods built step-by-step in PyTorch

Key Features

• 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

Book Description

PyTorch Deep Learning Hands-On is a book for engineers who want a fast-paced guide to doing deep learning work with Pytorch. It is not an academic textbook and does not try to teach deep learning principles. The book will help you most if you want to get your hands dirty and put PyTorch to work quickly.

PyTorch Deep Learning Hands-On shows how to implement the major deep learning architectures in PyTorch. It covers neural networks, computer vision, CNNs, 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 how the model works, before sharing the code you need to implement them in PyTorch.

This book is ideal if you want to rapidly add PyTorch to your deep learning toolset.

What you will 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

Who this book is for

Machine learning engineers who want to put PyTorch to work.

© 2019 Packt Publishing (Rafbók): 9781788833431

Útgáfudagur

Rafbók: 30 april 2019

Aðrir höfðu einnig áhuga á...

Veldu áskrift

  • Yfir 900.000 hljóð- og rafbækur

  • Yfir 400 titlar frá Storytel Original

  • Barnvænt viðmót með Kids Mode

  • Vistaðu bækurnar fyrir ferðalögin

Vinsælast

Unlimited

Besti valkosturinn fyrir einn notanda

3290 kr /mánuði
3 dagar frítt
  • 1 aðgangur

  • Ótakmörkuð hlustun

  • Yfir 900.000 hljóð- og rafbækur

  • Engin skuldbinding

  • Getur sagt upp hvenær sem er

Prófaðu frítt

Family

Fyrir þau sem vilja deila sögum með fjölskyldu og vinum.

Frá 3990 kr/mánuði
3 dagar frítt
  • 2-6 aðgangar

  • 100 klst/mán fyrir hvern aðgang

  • Yfir 900.000 hljóð- og rafbækur

  • ‎Engin skuldbinding

  • Getur sagt upp hvenær sem er

2 aðgangar

3990 kr /á mánuði
Prófaðu frítt