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Specialist Periodical Reports provide systematic and critical
review coverage in major areas of chemical research. Compiled by
teams of leading authorities in the relevant subject, the series
creates a unique service for the active research chemist with
regular critical in-depth accounts of progress in particular areas
of chemistry. Subject coverage of all volumes is very similar and
publication is on an annual or biennial basis. As EPR continues to
find new applications in virtually all areas of modern science,
including physics, chemistry, biology and materials science, this
series caters not only for experts in the field, but also those
wishing to gain a general overview of EPR applications in a given
area.
How can HR practitioners with little or no experience of analytics
feel confident in their ability to find, analyse and use workforce
data to make better business decisions? This book has the answers.
An understanding of people analytics is a crucial skill for all HR
professionals. This new edition provides expert guidance on the key
aspects of analytics, enabling all HR professionals to feel
confident in their ability to handle employee and organizational
data. It features new material on applying data to respond to
external disruption such as COVID-19 as well as how to develop a
people analytics journey. There is also advice on recruiting people
analytics specialists and embedding new data-driven operating
models within HR. This book is essential reading for all HR
professionals to develop understanding of how and where HR
analytics can make a tangible difference to organizations. With
updated case studies and thought leadership examples from companies
including NHS, AstraZeneca and Swarovski, this book demonstrates
how people analytics can be leveraged to improve culture and
employee engagement, increase performance and reduce costs.
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Panipat (Paperback)
Vishwas Patil; Translated by Nadeem Khan
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R750
R638
Discovery Miles 6 380
Save R112 (15%)
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Ships in 10 - 15 working days
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How can HR practitioners with little or no experience of analytics
feel confident in their ability to find, analyse and use workforce
data to make better business decisions? This book has the answers.
An understanding of people analytics is a crucial skill for all HR
professionals. This new edition provides expert guidance on the key
aspects of analytics, enabling all HR professionals to feel
confident in their ability to handle employee and organizational
data. It features new material on applying data to respond to
external disruption such as COVID-19 as well as how to develop a
people analytics journey. There is also advice on recruiting people
analytics specialists and embedding new data-driven operating
models within HR. This book is essential reading for all HR
professionals to develop understanding of how and where HR
analytics can make a tangible difference to organizations. With
updated case studies and thought leadership examples from companies
including NHS, AstraZeneca and Swarovski, this book demonstrates
how people analytics can be leveraged to improve culture and
employee engagement, increase performance and reduce costs.
Machine Learning for Future Fiber-Optic Communication Systems
provides a comprehensive and in-depth treatment of machine learning
concepts and techniques applied to key areas within optical
communications and networking, reflecting the state-of-the-art
research and industrial practices. The book gives knowledge and
insights into the role machine learning-based mechanisms will soon
play in the future realization of intelligent optical network
infrastructures that can manage and monitor themselves, diagnose
and resolve problems, and provide intelligent and efficient
services to the end users. With up-to-date coverage and extensive
treatment of various important topics related to machine learning
for fiber-optic communication systems, this book is an invaluable
reference for photonics researchers and engineers. It is also a
very suitable text for graduate students interested in ML-based
signal processing and networking.
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