000			02878nam a22002297a 4500
999			_c4036 _d4036
005			20221115153949.0
008			221026b ||||| |||| 00| 0 eng d
020			_a9789354240027
082			_a332.64524 _bMOT
100			_aMotwani, Bharti _94710
245			_aHR analytics: _bpractical approach using python
260			_bWiley India Pvt. Ltd. _aNew Delhi _c2021
300			_axxii, 627 p.
365			_aINR _b619.30
504			_aTable of content Section I HR Data Exploration, Extraction, and Visualization Chapter 1 HR Analytics and Python Chapter 2 Employee Data Exploration Using Core Modules and Libraries Chapter 3 Employee Data Visualization and Dashboards Using Core Libraries Chapter 4 Employee Data Extraction Using SQL Section II HR Analytics Using Basic Statistical Techniques Chapter 5 Design Compensation and Benefit Plan Using Conjoint Analysis Chapter 6 Forecast HR Cost Using Time Series Modeling (ARIMA) Chapter 7 Manpower Planning Using Monte Carlo Simulation and Markov Chain Chapter 8 Evaluate Training and Development Programs Using Compare Means Section III HR Analytics Using Unsupervised Machine Learning Chapter 9 Identify Association of Employee Job Satisfaction Using Association Rule Chapter 10 Determine Factors of Performance Appraisal System Using Dimension Reduction Algorithms Chapter 11 Assess Employee Absenteeism Using Clustering Techniques Section IV HR Analytics Using Supervised Machine Learning Chapter 12 Predict Employee Salary/Pay Rate Using Supervised Machine Learning Regression Techniques Chapter 13 Predict Employee Attrition Using Supervised Machine Learning Classification Techniques Chapter 14 Predict Employee Promotion Using Neural Network Model Section V HR Analytics for Text and Image Data Chapter 15 Review Resume Using Text Mining Chapter 16 Evaluate Employee Reviews Using Sentiment Analysis Chapter 17 Automate HR Help Desk Using Chatbots Chapter 18 Employee Recruitment and Selection Using Recommendation System Chapter 19 Measure Employee Happiness Using Image Data Processing
520			_aDescription HR Analytics: Practical Approach Using Python will enable readers gain sufficient knowledge and experience to perform analysis of data related to different processes executed in the HR department. Different tools and techniques available in Python for gaining an insight related to numeric, text and image data of current and prospective employees have been discussed in the book. In order to provide a more meaningful and easier learning experience, this book has been written with more interesting and relevant real-life examples.
650			_aHedge funds _91939
650			_aInvestment advisors _92942
650			_aHedging (Finance) _95269
650			_aCapitalists and financiers _92602
942			_2ddc _cBK