標(biāo)題: Titlebook: Business Analytics for Professionals; Alp Ustundag,Emre Cevikcan,Omer Faruk Beyca Book 2022 The Editor(s) (if applicable) and The Author(s [打印本頁] 作者: 小巷 時間: 2025-3-21 18:11
書目名稱Business Analytics for Professionals影響因子(影響力)
書目名稱Business Analytics for Professionals影響因子(影響力)學(xué)科排名
書目名稱Business Analytics for Professionals網(wǎng)絡(luò)公開度
書目名稱Business Analytics for Professionals網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Business Analytics for Professionals被引頻次
書目名稱Business Analytics for Professionals被引頻次學(xué)科排名
書目名稱Business Analytics for Professionals年度引用
書目名稱Business Analytics for Professionals年度引用學(xué)科排名
書目名稱Business Analytics for Professionals讀者反饋
書目名稱Business Analytics for Professionals讀者反饋學(xué)科排名
作者: CLAMP 時間: 2025-3-22 00:16 作者: defenses 時間: 2025-3-22 01:01
Business Analytics for Professionals978-3-030-93823-9Series ISSN 1860-5168 Series E-ISSN 2196-1735 作者: 妨礙 時間: 2025-3-22 07:47 作者: agnostic 時間: 2025-3-22 11:13
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.作者: 不如屎殼郎 時間: 2025-3-22 14:54
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.作者: MURKY 時間: 2025-3-22 18:59 作者: 無可爭辯 時間: 2025-3-22 22:56
Springer Series in Advanced Manufacturinghttp://image.papertrans.cn/b/image/192032.jpg作者: 指令 時間: 2025-3-23 01:32
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.作者: BUCK 時間: 2025-3-23 08:02 作者: 長矛 時間: 2025-3-23 10:52
Belief, Synonymy, and the , Distinction,In the age of big data, organizations and businesses have had to manage and make sense of data generated by a wide variety of systems, processes and transactions. The data contained in traditional relational databases is rather small compared to various sensor or social media data.作者: scotoma 時間: 2025-3-23 14:30 作者: lesion 時間: 2025-3-23 21:22 作者: prick-test 時間: 2025-3-24 01:37
The Chewa Logical Concept of TruthWith the advent of the Industry 4.0 revolution, the manufacturing industry uses analytics enhanced with real-time production data to enable and maintain enterprise-wide automation as well as making better and faster decisions.作者: curettage 時間: 2025-3-24 02:48
Prediction ModelingPredictive 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.作者: averse 時間: 2025-3-24 08:41
Time Series AnalysisThe emergence of digital technologies has been changing how things are done in the workplace, in society, and even at home. Recent technological advancements enable the instantaneous recording, processing, and dissemination of information and therefore decision-making processes become more efficient and effective.作者: ALTER 時間: 2025-3-24 14:30 作者: 防銹 時間: 2025-3-24 16:55 作者: sorbitol 時間: 2025-3-24 21:09
Human Resources AnalyticsHuman resource analytics is a special part of analytics where the main focus is the human resource. In HR analytics, the analytical process is applied to the organization’s human resources.作者: 拋媚眼 時間: 2025-3-25 02:21 作者: 克制 時間: 2025-3-25 06:00 作者: 裙帶關(guān)系 時間: 2025-3-25 10:03
The Semiotics of Social Identity,tions, statistical inference, and Bayesian statistics are explained. Along with theory, practical applications on a sample data set are provided. Applications are performed using the following Python libraries: Pandas, Seaborn, and Statmodels.作者: Predigest 時間: 2025-3-25 15:30 作者: 符合你規(guī)定 時間: 2025-3-25 19:34
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.作者: 是他笨 時間: 2025-3-25 23:55
Husserl’s Critique of Double Judgmentsture using large amounts of data. In this process, prescriptive analytics combines the output of predictive analytics and uses artificial intelligence, optimization algorithms, and expert systems to provide adaptive, automated, constrained, time-bound, and optimal decisions, thus having the potentia作者: CESS 時間: 2025-3-26 02:52
Introduction: The Proscriptive Principle,a platforms, our phones and computers, healthcare gadgets and wearable technology, scientific instruments, financial institutions, the manufacturing industry, news channels and more. When these small and wide data are analyzed, it offers businesses the opportunity to take quick action in business-de作者: MORT 時間: 2025-3-26 08:00
Agents and Patients in Dickens,product or service in order to reduce costs and avoid shortages. Supply chain analytics is the term that refers to the analytical decision-making processes using huge amount of data generated through the supply chain. Analytics in the supply chain is a critical component of SCM. Descriptive, predict作者: 圣人 時間: 2025-3-26 11:50
Agency and Scene in Jane Austen,eliver value to profitable customers. It involves internal business processes and functions (such as marketing, sales) as well as external influences (such as competitors). CRM systems collect, analyze and model information about customers using data science methods at all stages of their life cycle作者: 傳染 時間: 2025-3-26 15:40
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作者: 群島 時間: 2025-3-26 17:22
https://doi.org/10.1007/978-3-030-93823-9Business Analytics; Data Science; Intelligent Automation; Big Data; Machine Learning作者: apiary 時間: 2025-3-26 23:56
978-3-030-93825-3The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: modifier 時間: 2025-3-27 03:11
Descriptive Analyticstions, statistical inference, and Bayesian statistics are explained. Along with theory, practical applications on a sample data set are provided. Applications are performed using the following Python libraries: Pandas, Seaborn, and Statmodels.作者: 驚奇 時間: 2025-3-27 08:00
Feature Engineeringmodel 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.作者: 種類 時間: 2025-3-27 11:46
Financial Analyticselping 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.作者: Cupidity 時間: 2025-3-27 14:03 作者: vasospasm 時間: 2025-3-27 19:36 作者: 壟斷 時間: 2025-3-28 00:24 作者: Genteel 時間: 2025-3-28 03:36
Neural Networks and Deep Learningking mechanism by artificially forming a neural network. In this book, artificial neural networks are referred to as neural networks. The principal idea of a neural network is to show transformation between input and output as connections between neurons in a sequence (arrangement) of layers (White 作者: lipoatrophy 時間: 2025-3-28 07:35
Feature Engineeringmodel 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.作者: 愛哭 時間: 2025-3-28 11:19
Prescriptive Analytics: Optimization and Modelingture using large amounts of data. In this process, prescriptive analytics combines the output of predictive analytics and uses artificial intelligence, optimization algorithms, and expert systems to provide adaptive, automated, constrained, time-bound, and optimal decisions, thus having the potentia作者: 搏斗 時間: 2025-3-28 18:28
Big Data Management and Technologiesa platforms, our phones and computers, healthcare gadgets and wearable technology, scientific instruments, financial institutions, the manufacturing industry, news channels and more. When these small and wide data are analyzed, it offers businesses the opportunity to take quick action in business-de作者: 開玩笑 時間: 2025-3-28 19:23 作者: infantile 時間: 2025-3-29 01:43
CRM and Marketing Analyticseliver value to profitable customers. It involves internal business processes and functions (such as marketing, sales) as well as external influences (such as competitors). CRM systems collect, analyze and model information about customers using data science methods at all stages of their life cycle作者: languor 時間: 2025-3-29 05:21
Financial Analyticselping 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作者: 廢止 時間: 2025-3-29 11:04
Book 2022llustrates 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. .作者: 甜食 時間: 2025-3-29 12:56 作者: Palpate 時間: 2025-3-29 16:54
1860-5168 nes business problems concerning supply chain, marketing & CRM, financial, manufacturing and human resources functions and supplies solutions in Python. .978-3-030-93825-3978-3-030-93823-9Series ISSN 1860-5168 Series E-ISSN 2196-1735 作者: olfction 時間: 2025-3-29 21:04
The Distinction , in Medieval Semantics, Totowa, NJ, 2010). The first is that without domain expertise, neural networks may assist in estimating function structures and parameters (Si in Data Mining Techniques for the Life Sciences, Humana Press, Totowa, NJ, 2010).作者: 娘娘腔 時間: 2025-3-30 00:01
Neural Networks and Deep Learning Totowa, NJ, 2010). The first is that without domain expertise, neural networks may assist in estimating function structures and parameters (Si in Data Mining Techniques for the Life Sciences, Humana Press, Totowa, NJ, 2010).作者: inflate 時間: 2025-3-30 06:38 作者: BLANK 時間: 2025-3-30 11:49 作者: 細(xì)絲 時間: 2025-3-30 15:32 作者: Amenable 時間: 2025-3-30 19:34 作者: 兇兆 時間: 2025-3-30 23:25
Prescriptive Analytics: Optimization and Modeling, optimization algorithms, and expert systems to provide adaptive, automated, constrained, time-bound, and optimal decisions, thus having the potential to bring the greatest intelligence and value to businesses.作者: Lament 時間: 2025-3-31 01:42 作者: 駕駛 時間: 2025-3-31 08:18 作者: DAFT 時間: 2025-3-31 12:28 作者: PRO 時間: 2025-3-31 14:28
10樓作者: 混合 時間: 2025-3-31 19:46
10樓作者: accrete 時間: 2025-4-1 01:28
10樓
