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You're reading from  Caffe2 Quick Start Guide

Product typeBook
Published inMay 2019
Reading LevelBeginner
PublisherPackt
ISBN-139781789137750
Edition1st Edition
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Ashwin Nanjappa
Ashwin Nanjappa
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Ashwin Nanjappa

Ashwin Nanjappa is a senior architect at NVIDIA, working in the TensorRT team on improving deep learning inference on GPU accelerators. He has a PhD from the National University of Singapore in developing GPU algorithms for the fundamental computational geometry problem of 3D Delaunay triangulation. As a post-doctoral research fellow at the BioInformatics Institute (Singapore), he developed GPU-accelerated machine learning algorithms for pose estimation using depth cameras. As an algorithms research engineer at Visenze (Singapore), he implemented computer vision algorithm pipelines in C++, developed a training framework built upon Caffe in Python, and trained deep learning models for some of the world's most popular online shopping portals.
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Caffe2 in the cloud using containers

Containers are now a ubiquitous and necessary tool for robustly deploying software in production, both locally and in the cloud. They enable developers to create the ideal software environment for the application and ensure that this software environment is exactly replicated on developer workstations, test computers, staging computers, and the final deployment to local servers or instances in the cloud. Containers also help create a sanitized software environment for every single application, enabling multiple software environments, one for each application, when multiple applications are running on the same server.

Among the many available container tools, Docker is the most popular. We will focus on using Docker in this section. Docker is available for all popular Linux distributions, macOS X, and Windows. With Docker, you can create an...

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Caffe2 Quick Start Guide
Published in: May 2019Publisher: PacktISBN-13: 9781789137750

Author (1)

author image
Ashwin Nanjappa

Ashwin Nanjappa is a senior architect at NVIDIA, working in the TensorRT team on improving deep learning inference on GPU accelerators. He has a PhD from the National University of Singapore in developing GPU algorithms for the fundamental computational geometry problem of 3D Delaunay triangulation. As a post-doctoral research fellow at the BioInformatics Institute (Singapore), he developed GPU-accelerated machine learning algorithms for pose estimation using depth cameras. As an algorithms research engineer at Visenze (Singapore), he implemented computer vision algorithm pipelines in C++, developed a training framework built upon Caffe in Python, and trained deep learning models for some of the world's most popular online shopping portals.
Read more about Ashwin Nanjappa