[PDF][PDF] The age of analytics: Competing in a data-driven world
N Henke, L Jacques Bughin - 2016 - dln.jaipuria.ac.in
Five years ago, the McKinsey Global Institute (MGI) released Big data: The next frontier for
innovation, competition, and productivity. In the years since, data science has continued to …
innovation, competition, and productivity. In the years since, data science has continued to …
[HTML][HTML] A survey on deploying mobile deep learning applications: A systemic and technical perspective
With the rapid development of mobile devices and deep learning, mobile smart applications
using deep learning technology have sprung up. It satisfies multiple needs of users, network …
using deep learning technology have sprung up. It satisfies multiple needs of users, network …
Edge intelligence: The confluence of edge computing and artificial intelligence
Along with the rapid developments in communication technologies and the surge in the use
of mobile devices, a brand-new computation paradigm, edge computing, is surging in …
of mobile devices, a brand-new computation paradigm, edge computing, is surging in …
Deep convolutional computation model for feature learning on big data in internet of things
Currently, a large number of industrial data, usually referred to big data, are collected from
Internet of Things (IoT). Big data are typically heterogeneous, ie, each object in big datasets …
Internet of Things (IoT). Big data are typically heterogeneous, ie, each object in big datasets …
A blockchain-based machine learning framework for edge services in IIoT
Edge services provide an effective and superior means of real-time transmissions and rapid
processing of information in the Industrial Internet of Things (IIoT). However, the continuous …
processing of information in the Industrial Internet of Things (IIoT). However, the continuous …
Mobile-edge-computing-based hierarchical machine learning tasks distribution for IIoT
In this article, we propose a novel framework of mobile edge computing (MEC)-based
hierarchical machine learning (ML) tasks distribution for the Industrial Internet of Things. It is …
hierarchical machine learning (ML) tasks distribution for the Industrial Internet of Things. It is …
Toward collaborative inferencing of deep neural networks on Internet-of-Things devices
Recent advancements in deep neural networks (DNNs) have enabled us to solve
traditionally challenging problems. To deploy a service based on DNNs, since DNNs are …
traditionally challenging problems. To deploy a service based on DNNs, since DNNs are …