|
Showing 1 - 6 of
6 matches in All Departments
Cloud based Multi-Modal Information Analytics: A Hands-on Approach
discusses the various modalities of data and provide an aggregated
solutions using cloud. It includes the fundamentals of neural
networks, different types and how it can be used for the
multi-modal information analytics. The various application areas
that are image-centric and video are also presented with deployment
solutions in the cloud. Features Life cycle of the multi- modal
data analytics is discussed with applications of modalities of
text, image, and video. Deep Learning fundamentals and
architectures covering CNN, RNN and its types for learning for
different multi-modal networks. Applications of Multi-Modal
Analytics covering Text , Speech, and Image. This book is aimed at
researchers in Multi-modal analytics and related areas
This book reimagines education in today’s Artificial
Intelligence (AI) world and the Fourth Industrial Revolution.
Artificial intelligence will drastically affect every industry and
sector, and education is no exception. This book aims at how AI may
impact the teaching and learning process in education. This book is
designed to demystify AI for teachers and learners. This book will
help improve education and support institutions in the phenomena of
the emergence of AI in teaching and learning. This book presents a
comprehensive study of how AI improves teaching and learning, from
AI-based learning platforms to AI-assisted proctored examinations.
This book provides educators, learners, and administrators on how
AI makes sense in their everyday practice. Describing the
application of AI in ten key aspects, this comprehensive volume
prepares educational leaders, designers, researchers, and
policymakers to effectively rethink the teaching and learning
process and environments that students need to thrive. The readers
of this book never fall behind the fast pace and promising
innovations of today’s most advanced learning technology.
This book A Beginner's Guide to Learning Analytics is designed to
meet modern educational trends' needs. It is addressed to readers
who have no prior knowledge of learning analytics and functions as
an introductory text to learning analytics for those who want to do
more with evaluation/assessment in their organizations. The book is
useful to all who need to evaluate their learning and teaching
strategies. It aims to bring greater efficiency and deeper
engagement to individual students, learning communities, and
educators. Covered here are the key concepts linked to learning
analytics for researchers and practitioners interested in learning
analytics. This book helps those who want to apply analytics to
learning and development programs and helps educational
institutions to identify learners who require support and provide a
more personalized learning experience. Like chapters show diverse
uses of learning analytics to enhance student and faculty
performance. It presents a coherent framework for the effective
translation of learning analytics research for educational practice
to its practical application in different educational domains. This
book provides educators and researchers with the tools and
frameworks to effectively make sense of and use data and analytics
in their everyday practice. This book will be a valuable addition
to researchers' bookshelves.
This book A Beginner's Guide to Learning Analytics is designed to
meet modern educational trends' needs. It is addressed to readers
who have no prior knowledge of learning analytics and functions as
an introductory text to learning analytics for those who want to do
more with evaluation/assessment in their organizations. The book is
useful to all who need to evaluate their learning and teaching
strategies. It aims to bring greater efficiency and deeper
engagement to individual students, learning communities, and
educators. Covered here are the key concepts linked to learning
analytics for researchers and practitioners interested in learning
analytics. This book helps those who want to apply analytics to
learning and development programs and helps educational
institutions to identify learners who require support and provide a
more personalized learning experience. Like chapters show diverse
uses of learning analytics to enhance student and faculty
performance. It presents a coherent framework for the effective
translation of learning analytics research for educational practice
to its practical application in different educational domains. This
book provides educators and researchers with the tools and
frameworks to effectively make sense of and use data and analytics
in their everyday practice. This book will be a valuable addition
to researchers' bookshelves.
Big data generates around us constantly from daily business, custom
use, engineering, and science activities. Sensory data is collected
from the internet of things (IoT) and cyber-physical systems (CPS).
Merely storing such a massive amount of data is meaningless, as the
key point is to identify, locate, and extract valuable knowledge
from big data to forecast and support services. Such extracted
valuable knowledge is usually referred to as smart data. It is
vital to providing suitable decisions in business, science, and
engineering applications. Deep Learning Applications for
Cyber-Physical Systems provides researchers a platform to present
state-of-the-art innovations, research, and designs while
implementing methodological and algorithmic solutions to data
processing problems and designing and analyzing evolving trends in
health informatics and computer-aided diagnosis in deep learning
techniques in context with cyber physical systems. Covering topics
such as smart medical systems, intrusion detection systems, and
predictive analytics, this text is essential for computer
scientists, engineers, practitioners, researchers, students, and
academicians, especially those interested in the areas of internet
of things, machine learning, deep learning, and cyber-physical
systems.
Big data generates around us constantly from daily business, custom
use, engineering, and science activities. Sensory data is collected
from the internet of things (IoT) and cyber-physical systems (CPS).
Merely storing such a massive amount of data is meaningless, as the
key point is to identify, locate, and extract valuable knowledge
from big data to forecast and support services. Such extracted
valuable knowledge is usually referred to as smart data. It is
vital to providing suitable decisions in business, science, and
engineering applications. Deep Learning Applications for
Cyber-Physical Systems provides researchers a platform to present
state-of-the-art innovations, research, and designs while
implementing methodological and algorithmic solutions to data
processing problems and designing and analyzing evolving trends in
health informatics and computer-aided diagnosis in deep learning
techniques in context with cyber physical systems. Covering topics
such as smart medical systems, intrusion detection systems, and
predictive analytics, this text is essential for computer
scientists, engineers, practitioners, researchers, students, and
academicians, especially those interested in the areas of internet
of things, machine learning, deep learning, and cyber-physical
systems.
|
You may like...
Ab Wheel
R209
R149
Discovery Miles 1 490
|