標(biāo)題: Titlebook: Essentials of Business Analytics; An Introduction to t Bhimasankaram Pochiraju,Sridhar Seshadri Textbook 2019 Springer Nature Switzerland A [打印本頁] 作者: 貪污 時(shí)間: 2025-3-21 17:58
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書目名稱Essentials of Business Analytics讀者反饋
書目名稱Essentials of Business Analytics讀者反饋學(xué)科排名
作者: 笨拙的我 時(shí)間: 2025-3-21 23:17
Data Collectionf the characteristics of the data in question. How do we collect data? What kinds of data exist? Where is it coming from? Before beginning to analyze data, analysts must know how to answer these questions. In doing so, we build the base upon which the rest of our examination follows. This chapter ai作者: 爭論 時(shí)間: 2025-3-22 00:45
Data Management—Relational Database Systems (RDBMS)at can be stored and processed by computers. In order to process and manipulate data efficiently, it is very important that data is stored in an appropriate form. Data comes in many shapes and forms, and some of the most commonly known forms of data are numbers, text, images, and videos. Depending o作者: RODE 時(shí)間: 2025-3-22 04:44 作者: FOLLY 時(shí)間: 2025-3-22 10:16 作者: HACK 時(shí)間: 2025-3-22 15:45
Statistical Methods: Basic Inferencesrder to do this, we must be able to summarize and lay out datasets in a manner that allows us to use more advanced methods of examination. This chapter introduces fundamental methods of statistics, such as the central limit theorem, confidence intervals, hypothesis testing and analysis of variance (作者: HACK 時(shí)間: 2025-3-22 19:25
Statistical Methods: Regression Analysis systematically develop linear regression modeling of data. Chapter 6 on Basic inference is all the prerequisite that is required for this chapter. We start with motivating examples (Sect.?2). Section 3 deals with the methods and diagnostics for linear regression. We start with a discussion on what 作者: 窩轉(zhuǎn)脊椎動(dòng)物 時(shí)間: 2025-3-22 21:57
Text Analyticserstanding and examining data in word formats, which tend to be more unstructured and therefore more complex. Text analytics uses tools such as those embedded in R in order to extract meaning from large amounts of word-based data. Two methods are described in this chapter: bag-of-words and natural l作者: 背叛者 時(shí)間: 2025-3-23 05:03
Simulationg. Our focus will be on applications and to understand the steps in building a simulation model and interpreting the results of the model; the theoretical background can be found in the reference textbooks described at the end of the chapter. Simulation is a practical approach to decision making und作者: 珊瑚 時(shí)間: 2025-3-23 06:17 作者: nurture 時(shí)間: 2025-3-23 12:08 作者: 輕快來事 時(shí)間: 2025-3-23 14:30
Machine Learning (Unsupervised) business processes, or resulting from individual or collective behavior of people or systems. This observed sample data (e.g., the falling of the apple) contains a view of reality (e.g., the laws of gravity) that generates it. .作者: precede 時(shí)間: 2025-3-23 18:48
Machine Learning (Supervised)assive cloud platform, driving billions of decisions every day. Machine learning has many paradigms. In this chapter, we explore the philosophical, theoretical, and practical aspects of one of the most common machine learning paradigms—.—that essentially learns a mapping from an . (e.g., symptoms an作者: 豐滿有漂亮 時(shí)間: 2025-3-24 01:04
Deep Learningg is a rapidly growing area of machine learning. Machine learning (ML) has seen numerous successes, but applying traditional ML algorithms today often means spending a long time hand-engineering the domain-specific input feature representation. This is true for many problems in vision, audio, natura作者: hangdog 時(shí)間: 2025-3-24 05:39
https://doi.org/10.1007/978-3-319-68837-4Business Analtyics; Big Data; Data Analysis; Data Visualization; Forecasting Analytics; Machine Learning; 作者: PALL 時(shí)間: 2025-3-24 10:32
Smart-Grid Modelling and Simulationrder to do this, we must be able to summarize and lay out datasets in a manner that allows us to use more advanced methods of examination. This chapter introduces fundamental methods of statistics, such as the central limit theorem, confidence intervals, hypothesis testing and analysis of variance (ANOVA).作者: Myocyte 時(shí)間: 2025-3-24 13:11 作者: FID 時(shí)間: 2025-3-24 17:27
J. Woody Sistrunk MD,Frits van der Haar PhD business processes, or resulting from individual or collective behavior of people or systems. This observed sample data (e.g., the falling of the apple) contains a view of reality (e.g., the laws of gravity) that generates it. .作者: 蕨類 時(shí)間: 2025-3-24 19:09
Statistical Methods: Basic Inferencesrder to do this, we must be able to summarize and lay out datasets in a manner that allows us to use more advanced methods of examination. This chapter introduces fundamental methods of statistics, such as the central limit theorem, confidence intervals, hypothesis testing and analysis of variance (ANOVA).作者: optic-nerve 時(shí)間: 2025-3-25 02:58 作者: 離開就切除 時(shí)間: 2025-3-25 06:53
Machine Learning (Unsupervised) business processes, or resulting from individual or collective behavior of people or systems. This observed sample data (e.g., the falling of the apple) contains a view of reality (e.g., the laws of gravity) that generates it. .作者: 臭了生氣 時(shí)間: 2025-3-25 07:41
Bhimasankaram Pochiraju,Sridhar SeshadriOffers a comprehensive introductory approach to business analytics that includes an emphasis on big data handling, applications in different verticals and case studies.Highlights big data handling, ap作者: 厭食癥 時(shí)間: 2025-3-25 11:38 作者: 充足 時(shí)間: 2025-3-25 19:05 作者: 認(rèn)識(shí) 時(shí)間: 2025-3-25 23:41 作者: terazosin 時(shí)間: 2025-3-26 01:57 作者: 人類的發(fā)源 時(shí)間: 2025-3-26 07:30
P. Madhumathy,Shweta Babu Prasaddustry, be it healthcare, life sciences, finance, insurance, education, entertainment, retail, etc. The Digital Revolution, also known as the Third Industrial Revolution, started in the 1980s and sparked the advancement and evolution of technology from analog electronic and mechanical devices to the作者: colloquial 時(shí)間: 2025-3-26 12:05 作者: Cerebrovascular 時(shí)間: 2025-3-26 13:24 作者: Daily-Value 時(shí)間: 2025-3-26 18:59 作者: perjury 時(shí)間: 2025-3-26 22:54
Lukas Hick,Dirk B?rner,Henning Pagniaerstanding and examining data in word formats, which tend to be more unstructured and therefore more complex. Text analytics uses tools such as those embedded in R in order to extract meaning from large amounts of word-based data. Two methods are described in this chapter: bag-of-words and natural l作者: 欺騙世家 時(shí)間: 2025-3-27 04:20 作者: Consensus 時(shí)間: 2025-3-27 08:38
Aakashjit Bhattacharya,Debashis Deof visits of a patient to a particular physician; the number of visits of a customer to a store; etc. In such contexts, the analyst is interested in explaining and/or predicting such outcome variables on the basis of explanatory variables.作者: moratorium 時(shí)間: 2025-3-27 13:18
Web Cloud Communication Control,o other explanatory variables. The notion of “event” depends on the context and the applications. The event in question may be dealt as may happen in a biomedical context or churning in a business context or machine failure in an engineering context. Survival methods are characterized by “censoring”作者: 諂媚于性 時(shí)間: 2025-3-27 15:14 作者: 澄清 時(shí)間: 2025-3-27 20:58 作者: 擋泥板 時(shí)間: 2025-3-27 22:51
Development of Fetal Thyroid System Controlg is a rapidly growing area of machine learning. Machine learning (ML) has seen numerous successes, but applying traditional ML algorithms today often means spending a long time hand-engineering the domain-specific input feature representation. This is true for many problems in vision, audio, natura作者: Awning 時(shí)間: 2025-3-28 03:54 作者: BLUSH 時(shí)間: 2025-3-28 07:39 作者: 得罪人 時(shí)間: 2025-3-28 12:21 作者: 無節(jié)奏 時(shí)間: 2025-3-28 17:04 作者: concise 時(shí)間: 2025-3-28 21:02 作者: 暫時(shí)過來 時(shí)間: 2025-3-28 23:58 作者: Commonplace 時(shí)間: 2025-3-29 07:08
Textbook 2019 be used as a guide to the field by practitioners. The book has contributions from experts in top universities and industry. The editors have taken extreme care to ensure continuity across the chapters..The material is organized into three parts: A) Tools, B) Models and C) Applications. In Part A, t作者: Immunization 時(shí)間: 2025-3-29 11:12
0884-8289 verticals and case studies.Highlights big data handling, ap.This comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs. It can also be used as a guide to the field by practitioners. The book has contributions from experts作者: institute 時(shí)間: 2025-3-29 14:30 作者: 多嘴多舌 時(shí)間: 2025-3-29 19:13 作者: SOW 時(shí)間: 2025-3-29 20:13
https://doi.org/10.1007/978-3-030-90083-0ns of data storage—relational database management systems. We provide an introduction using which a reader can perform the essential operations. References for a deeper understanding are given at the end of the chapter.作者: 集聚成團(tuán) 時(shí)間: 2025-3-30 01:55
Lukas Hick,Dirk B?rner,Henning Pagniaf words. Its applications include clustering or segmentation of documents and sentiment analysis. Natural language processing uses the order and “type” of words to infer the meaning. Hence, NLP deals more with issues such as parts of speech.作者: FOLD 時(shí)間: 2025-3-30 04:30
Development of Fetal Thyroid System Controla good high-level abstract representation for the input. These algorithms are today enabling many groups to achieve groundbreaking results in vision recognition, speech recognition, language processing, robotics, and other areas.作者: 鞭子 時(shí)間: 2025-3-30 11:38 作者: 痛得哭了 時(shí)間: 2025-3-30 16:08 作者: 我們的面粉 時(shí)間: 2025-3-30 19:07 作者: 大約冬季 時(shí)間: 2025-3-31 00:19
Data Collectiondata, analysts must know how to answer these questions. In doing so, we build the base upon which the rest of our examination follows. This chapter aims to introduce and explain the nuances of data collection, so that we understand the methods we can use to analyze it.作者: 睨視 時(shí)間: 2025-3-31 00:58 作者: irreparable 時(shí)間: 2025-3-31 08:37
Sargam Yadav,Abhishek Kaushik,Shubham Sharmain applications in various disciplines and business verticals to be valuable. The bridge between the tools and the applications are the modeling methods used by managers and researchers in disciplines such as finance, marketing, and operations. This book provides coverage of all three aspects: tools, modeling methods, and applications.作者: 血友病 時(shí)間: 2025-3-31 10:07
Web Cloud Communication Control, by which the event in question may not have happened (at the time observations end) for certain observational units (cases) in the data; yet, such censored data are useful and are judiciously used in survival analysis. In that sense, survival analysis methods differ from techniques such as regression analysis.作者: blithe 時(shí)間: 2025-3-31 14:28
