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Titlebook: Business Analytics for Professionals; Alp Ustundag,Emre Cevikcan,Omer Faruk Beyca Book 2022 The Editor(s) (if applicable) and The Author(s

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发表于 2025-3-21 18:11:50 | 显示全部楼层 |阅读模式
期刊全称Business Analytics for Professionals
影响因子2023Alp Ustundag,Emre Cevikcan,Omer Faruk Beyca
视频videohttp://file.papertrans.cn/193/192032/192032.mp4
发行地址Explain concepts and techniques for business analytics.Demonstrates real applications in business and industry.Supplies models and solutions in Python
学科分类Springer Series in Advanced Manufacturing
图书封面Titlebook: Business Analytics for Professionals;  Alp Ustundag,Emre Cevikcan,Omer Faruk Beyca Book 2022 The Editor(s) (if applicable) and The Author(s
影响因子.This book explains concepts and techniques for business analytics and demonstrate them on real life applications for managers and practitioners. It illustrates how machine learning and optimization techniques can be used to implement intelligent business automation systems. The book examines business problems concerning supply chain, marketing & CRM, financial, manufacturing and human resources functions and supplies solutions in Python. .
Pindex Book 2022
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Business Analytics for Professionals978-3-030-93823-9Series ISSN 1860-5168 Series E-ISSN 2196-1735
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Motivations for an Internalist Semantics,model complexity and establish simple, accurate and robust models. Feature engineering is the process of using domain knowledge to extract input variables from raw data, prioritize them and select the best ones so that machine learning algorithms work well and model performance is improved.
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Meaning of Taboos Using Counterfactual Logicelping companies reduce risk and make more efficient financial decisions. Machine learning and advanced analytics are used in several financial applications such as fraud detection and prevention systems, credit risk modelling, financial statement analysis, algorithmic trading, robo-advisory systems etc.
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Springer Series in Advanced Manufacturinghttp://image.papertrans.cn/b/image/192032.jpg
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https://doi.org/10.1007/978-1-4615-4769-3Predictive modeling can be defined as modeling the historical data using statistical and machine learning techniques to predict future observations. Prediction modeling tasks can be grouped into three categories: supervised learning, unsupervised learning and reinforcement learning.
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