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Caffe2 Quick Start Guide
Caffe2 Quick Start Guide

Caffe2 Quick Start Guide: Modular and scalable deep learning made easy

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Caffe2 Quick Start Guide

Introduction and Installation

Welcome to the Caffe2 Quick Start Guide. This book aims to provide you with a quick introduction to the Caffe2 deep learning framework and how to use it for training and deployment of deep learning models. This book uses code samples to create, train, and run inference on actual deep learning models that solve real problems. In this way, its code can be applied quickly by readers to their own applications.

This chapter provides a brief introduction to Caffe2 and shows you how to build and install it on your computer. In this chapter, we will cover the following topics:

  • Introduction to deep learning and Caffe2
  • Building and installing Caffe2
  • Testing Caffe2 Python API
  • Testing Caffe2 C++ API
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Download code icon Download Code

Key benefits

  • Migrate models trained with other deep learning frameworks to Caffe2
  • Integrate Caffe2 with Android or iOS, and implement deep learning models for mobile devices
  • Leverage the distributed capabilities of Caffe2 to build models that scale easily

Description

Caffe2 is a popular deep learning library used for fast and scalable training, and inference of deep learning models on different platforms. This book introduces you to the Caffe2 framework and demonstrates how you can leverage its power to build, train, and deploy efficient neural network models at scale. The Caffe 2 Quick Start Guide will help you in installing Caffe2, composing networks using its operators, training models, and deploying models to different architectures. The book will also guide you on how to import models from Caffe and other frameworks using the ONNX interchange format. You will then cover deep learning accelerators such as CPU and GPU and learn how to deploy Caffe2 models for inference on accelerators using inference engines. Finally, you'll understand how to deploy Caffe2 to a diverse set of hardware, using containers on the cloud and resource-constrained hardware such as Raspberry Pi. By the end of this book, you will not only be able to compose and train popular neural network models with Caffe2, but also deploy them on accelerators, to the cloud and on resource-constrained platforms such as mobile and embedded hardware.

Who is this book for?

Data scientists and machine learning engineers who wish to create fast and scalable deep learning models in Caffe2 will find this book to be very useful. Some understanding of the basic machine learning concepts and prior exposure to programming languages like C++ and Python will be useful.

What you will learn

  • Build and install Caffe2
  • Compose neural networks
  • Import deep learning models from other frameworks
  • Train neural networks on a CPU or GPU
  • Deploy models at the edge and in the cloud
  • Import a neural network from Caffe
  • Deploy models on CPU or GPU accelerators using inference engines
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Publication date, Length, Edition, Language, ISBN-13
Publication date : May 31, 2019
Length: 136 pages
Edition : 1st
Language : English
ISBN-13 : 9781789137750
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Product Details

Publication date : May 31, 2019
Length: 136 pages
Edition : 1st
Language : English
ISBN-13 : 9781789137750
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Tools :

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Table of Contents

8 Chapters
Introduction and Installation Chevron down icon Chevron up icon
Composing Networks Chevron down icon Chevron up icon
Training Networks Chevron down icon Chevron up icon
Working with Caffe Chevron down icon Chevron up icon
Working with Other Frameworks Chevron down icon Chevron up icon
Deploying Models to Accelerators for Inference Chevron down icon Chevron up icon
Caffe2 at the Edge and in the cloud Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(2 Ratings)
5 star 100%
4 star 0%
3 star 0%
2 star 0%
1 star 0%
Merrill Aug 27, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Well written , highly informational .
Amazon Verified review Amazon
Shruti Aug 27, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great book for a beginner like me :)
Amazon Verified review Amazon
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All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


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