機械学習による人事データ分析入門：実務家、心理学者、組織のために Introducing HR Analytics with Machine Learning : Empowering Practitioners, Psychologists, and Organizations

機械学習による人事データ分析入門：実務家、心理学者、組織のために<br>Introducing HR Analytics with Machine Learning : Empowering Practitioners, Psychologists, and Organizations

個数：

機械学習による人事データ分析入門：実務家、心理学者、組織のために
Introducing HR Analytics with Machine Learning : Empowering Practitioners, Psychologists, and Organizations

Rosett, Christopher M./ Hagerty, Austin

ウェブストア価格 ¥28,777（本体¥26,161）
Springer Nature Switzerland AG（2021/06発売）
外貨定価 US$ 139.99
ポイント 261pt

提携先の海外書籍取次会社に在庫がございます。通常3週間で発送いたします。
【重要ご説明事項】
1. 納期遅延や、ご入手不能となる場合が若干ございます。
2. 複数冊ご注文の場合は、ご注文数量が揃ってからまとめて発送いたします。
3. 美品のご指定は承りかねます。

●3Dセキュア導入とクレジットカードによるお支払いについて

【入荷遅延について】
世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。

◆画像の表紙や帯等は実物とは異なる場合があります。

◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
また、洋書販売価格は、ご注文確定時点での日本円価格となります。
ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。

製本 Hardcover:ハードカバー版／ページ数 271 p.
商品コード 9783030676254

Full 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.

Part I: Introducing Machine Learning: Past and Present.- The Historical Lens of Sub-Fields.- The State of the People Data Industry.- Part II: The Science, Philosophy, and Legality of using Machine Learning with People Data.- Scientific Considerations when Working with Behavioral Data.- Legal and Ethical Considerations when Working with Employee Data.- Part III: - Instruction and Application of Machine Learning in an Employee Data Context.- Introduction and Overview of Stats and Computing.- Interpret and communicate.- Data Analyzing.- Data Wrangling.