Author: Christopher M. Rosett
Publisher: Springer Nature
ISBN: 3030676269
Category : Psychology
Languages : en
Pages : 266
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Book Description
This book directly addresses the explosion of literature about leveraging analytics with employee data and how organizational psychologists and practitioners can harness new information to help guide positive change in the workplace. In order for today’s organizational psychologists to successfully work with their partners they must go beyond behavioral science into the realms of computing and business acumen. Similarly, today’s data scientists must appreciate the unique aspects of behavioral data and the special circumstances which surround HR data and HR systems. Finally, traditional HR professionals must become familiar with research methods, statistics, and data systems in order to collaborate with these new specialized partners and teams. Despite the increasing importance of this diversity of skill, many organizations are still unprepared to build teams with the comprehensive skills necessary to have high performing HR Analytics functions. And importantly, all these considerations are magnified by the introduction and acceleration of machine learning in HR. This book will serve as an introduction to these areas and provide guidance on building the connectivity across domains required to establish well-rounded skills for individuals and best practices for organizations when beginning to apply advanced analytics to workforce data. It will also introduce machine learning and where it fits within the larger HR Analytics framework by explaining many of its basic tenets and methodologies. By the end of the book, readers will understand the skills required to do advanced HR analytics well, as well as how to begin designing and applying machine learning within a larger human capital strategy.
Author: Dr Martin R. Edwards
Publisher: Kogan Page Publishers
ISBN: 0749484454
Category : Business & Economics
Languages : en
Pages : 537
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Book Description
HR metrics and organizational people-related data are an invaluable source of information from which to identify trends and patterns in order to make effective business decisions. But HR practitioners often lack the statistical and analytical know-how to fully harness the potential of this data. Predictive HR Analytics provides a clear, accessible framework for understanding and working with people analytics and advanced statistical techniques. Using the statistical package SPSS (with R syntax included), it takes readers step by step through worked examples, showing them how to carry out and interpret analyses of HR data in areas such as employee engagement, performance and turnover. Readers are shown how to use the results to enable them to develop effective evidence-based HR strategies. This second edition has been updated to include the latest material on machine learning, biased algorithms, data protection and GDPR considerations, a new example using survival analyses, and up-to-the-minute screenshots and examples with SPSS version 25. It is supported by a new appendix showing main R coding, and online resources consisting of SPSS and Excel data sets and R syntax with worked case study examples.
Author: Andrew W. Trask
Publisher: Simon and Schuster
ISBN: 163835720X
Category : Computers
Languages : en
Pages : 492
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Book Description
Summary Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning. About the Book Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare! When you're done, you'll be fully prepared to move on to mastering deep learning frameworks. What's inside The science behind deep learning Building and training your own neural networks Privacy concepts, including federated learning Tips for continuing your pursuit of deep learning About the Reader For readers with high school-level math and intermediate programming skills. About the Author Andrew Trask is a PhD student at Oxford University and a research scientist at DeepMind. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning, where he trained the world's largest artificial neural network and helped guide the analytics roadmap for the Synthesys cognitive computing platform. Table of Contents Introducing deep learning: why you should learn it Fundamental concepts: how do machines learn? Introduction to neural prediction: forward propagation Introduction to neural learning: gradient descent Learning multiple weights at a time: generalizing gradient descent Building your first deep neural network: introduction to backpropagation How to picture neural networks: in your head and on paper Learning signal and ignoring noise:introduction to regularization and batching Modeling probabilities and nonlinearities: activation functions Neural learning about edges and corners: intro to convolutional neural networks Neural networks that understand language: king - man + woman == ? Neural networks that write like Shakespeare: recurrent layers for variable-length data Introducing automatic optimization: let's build a deep learning framework Learning to write like Shakespeare: long short-term memory Deep learning on unseen data: introducing federated learning Where to go from here: a brief guide
Author: Thomas H. Davenport
Publisher: Harvard Business Press
ISBN: 1422156303
Category : Business & Economics
Languages : en
Pages : 243
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Book Description
You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool. In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics.
Author: Jeffrey Paul Wheeler
Publisher: CRC Press
ISBN: 1003803679
Category : Mathematics
Languages : en
Pages : 891
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Book Description
The primary goal of this text is a practical one. Equipping students with enough knowledge and creating an independent research platform, the author strives to prepare students for professional careers. Providing students with a marketable skill set requires topics from many areas of optimization. The initial goal of this text is to develop a marketable skill set for mathematics majors as well as for students of engineering, computer science, economics, statistics, and business. Optimization reaches into many different fields. This text provides a balance where one is needed. Mathematics optimization books are often too heavy on theory without enough applications; texts aimed at business students are often strong on applications, but weak on math. The book represents an attempt at overcoming this imbalance for all students taking such a course. The book contains many practical applications but also explains the mathematics behind the techniques, including stating definitions and proving theorems. Optimization techniques are at the heart of the first spam filters, are used in self-driving cars, play a great role in machine learning, and can be used in such places as determining a batting order in a Major League Baseball game. Additionally, optimization has seemingly limitless other applications in business and industry. In short, knowledge of this subject offers an individual both a very marketable skill set for a wealth of jobs as well as useful tools for research in many academic disciplines. Many of the problems rely on using a computer. Microsoft’s Excel is most often used, as this is common in business, but Python and other languages are considered. The consideration of other programming languages permits experienced mathematics and engineering students to use MATLAB® or Mathematica, and the computer science students to write their own programs in Java or Python.
Author: Cengiz Kahraman
Publisher: Springer Nature
ISBN: 3031671929
Category :
Languages : en
Pages : 753
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Book Description
Author: Stacey Harris
Publisher: Kogan Page Publishers
ISBN: 1789665280
Category : Business & Economics
Languages : en
Pages : 209
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Book Description
Technology can have huge benefits for the HR function. Whether it's saving time by streamlining processes, boosting engagement by enabling analysis of people data or improving employee development by allowing staff to access the content they need on different platforms, wherever and whenever they need it; the opportunities are vast. However, with more apps, software and platforms than ever before, the volume and variety of available technologies can be overwhelming. This makes it extremely difficult for HR professionals to know where to start when assessing what technologies are out there and which are worth investing in. Introduction to HR Technologies addresses these issues in clear, accessible and jargon-free language and is an indispensable guide for HR professionals needing to get to grips with technologies and understand how to use them to add tangible business value. Covering all the core areas of HR including recruitment, performance management, learning and development (L&D) and reward, Introduction to HR Technologies allows practitioners to identify areas where technologies can be used to drive performance and what to look for when assessing technological solutions. There is also discussion of artificial intelligence (AI), machine learning and the Internet of Things (IoT) and what they mean for HR. This book is essential reading for all HR professionals looking to use technology confidently to increase performance, improve processes and add value to both employees and the business as a whole.
Author: Dr. Manisha L. Waghmode
Publisher: RK Publication
ISBN: 934802017X
Category : Business & Economics
Languages : en
Pages : 370
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Book Description
"HR Analytics for Business Excellence" explores the transformative power of data-driven decision-making in human resource management. This book provides comprehensive insights into leveraging analytics to enhance employee performance, optimize talent acquisition, and improve overall organizational effectiveness. It delves into key metrics, analytical tools, and case studies, illustrating how HR analytics can drive strategic initiatives, foster a culture of continuous improvement, and ultimately contribute to business success. By integrating analytics into HR practices, organizations can make informed decisions that align with their goals and enhance their competitive advantage.
Author: GUPTA, DEEPA
Publisher: PHI Learning Pvt. Ltd.
ISBN: 8119364562
Category : Business & Economics
Languages : en
Pages : 406
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Book Description
This book provides a comprehensive overview of various aspects of HR analytics. It delves into important definitions, the significance of HR analytics, methods of data collection and management, as well as specific areas such as recruitment analytics, performance management analytics, employee engagement analytics, and diversity, equity and inclusion (DEI) analytics. The book also explores ethical considerations, implementation strategies, and the role of HR analytics in workforce planning, succession planning, and employee wellness. Additionally, it discusses monitoring the impact of interventions and offers insights into the future of HR analytics. Besides, it offers a range of practical tools and templates for various applications. KEY FEATURES • Comprehensive coverage: Covers a wide range of topics related to HR analytics from the basics to more specialized areas. • Diverse tools and techniques: Includes discussions on various data analysis techniques, such as predictive analytics, machine learning, and statistical modelling. • Practical templates and forms: Inclusion of templates and forms, such as employee attitude surveys and KPI dashboards, make this book more hands-on and practical. • Ethical and legal considerations: Focusses on ethics and compliance/legal considerations for the evolving landscape of HR analytics. • Future-oriented content: Discusses on the future of HR analytics and emerging trends is a dimension of forward-looking. • Agile HR analytics: Includes Agile HR Analytics as an emerging trend. • Staying updated: Acknowledges the importance of staying updated on HR analytics trends. • Clarity and accessibility: Presents a clear, accessible, and engaging text making the book reader-friendly. • The book primarily intended to the students of business schools is equally valuable to the professionals in the field. For instructor’s resources, visit https://www.phindia.com/HR_ analytics_deepa_mukul_partha TARGET AUDIENCE • MBA — HR • Data Analytics and HR Professionals
Author: Bernard Marr
Publisher: Kogan Page Publishers
ISBN: 0749482478
Category : Business & Economics
Languages : en
Pages : 265
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Book Description
FINALIST: Business Book Awards 2019 - HR and Management Category Traditionally seen as a purely people function unconcerned with numbers, HR is now uniquely placed to use company data to drive performance, both of the people in the organization and the organization as a whole. Data-Driven HR is a practical guide which enables HR professionals to leverage the value of the vast amount of data available at their fingertips. Covering how to identify the most useful sources of data, collect information in a transparent way that is in line with data protection requirements and turn this data into tangible insights, this book marks a turning point for the HR profession. Covering all the key elements of HR including recruitment, employee engagement, performance management, wellbeing and training, Data-Driven HR examines the ways data can contribute to organizational success by, among other things, optimizing processes, driving performance and improving HR decision making. Packed with case studies and real-life examples, this is essential reading for all HR professionals looking to make a measurable difference in their organizations.
