標題: Titlebook: Data Science for Entrepreneurship; Principles and Metho Werner Liebregts,Willem-Jan van den Heuvel,Arjan v Textbook 2023 Springer Nature Sw [打印本頁] 作者: Carter 時間: 2025-3-21 20:01
書目名稱Data Science for Entrepreneurship影響因子(影響力)
書目名稱Data Science for Entrepreneurship影響因子(影響力)學(xué)科排名
書目名稱Data Science for Entrepreneurship網(wǎng)絡(luò)公開度
書目名稱Data Science for Entrepreneurship網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Science for Entrepreneurship被引頻次
書目名稱Data Science for Entrepreneurship被引頻次學(xué)科排名
書目名稱Data Science for Entrepreneurship年度引用
書目名稱Data Science for Entrepreneurship年度引用學(xué)科排名
書目名稱Data Science for Entrepreneurship讀者反饋
書目名稱Data Science for Entrepreneurship讀者反饋學(xué)科排名
作者: Granular 時間: 2025-3-21 21:38 作者: 抵消 時間: 2025-3-22 02:11 作者: 異端邪說2 時間: 2025-3-22 08:37 作者: Cerebrovascular 時間: 2025-3-22 11:19 作者: Nmda-Receptor 時間: 2025-3-22 13:50 作者: Nmda-Receptor 時間: 2025-3-22 19:31
Sequential Experimentation and Learninglearner selects actions that will generate new data which allow for future learning. Critically, it is assumed that only the data associated with the action taken by the learner is revealed: the potential outcomes of alternative actions are not disclosed. Generally, such sequential learning approach作者: Fantasy 時間: 2025-3-22 22:46 作者: commute 時間: 2025-3-23 03:28 作者: alcoholism 時間: 2025-3-23 08:41
Data-Driven Decision-Makingay that for securing data science impact, data science should start and end with an extensive analysis of the related decision-making. The full embedding of data science in decision-making is often labeled data-driven decision-making (DDDM). This includes the use of data and data science concepts in作者: 爭吵加 時間: 2025-3-23 12:26 作者: 極微小 時間: 2025-3-23 17:31
Strategy in the Era of Digital Disruptioned to make it happen. Therefore, this chapter starts off by explaining the notion of digital disruption and consecutively illustrating its pervasiveness using a number of detailed examples. It then offers a sneak peek of the processes happening behind the scenes of digital disruption. Specifically, 作者: PLAYS 時間: 2025-3-23 21:04
Digital Servitization in Agricultureknown examples of servitization are Atlas Copco’s compressed-air-as-a-service and Rolls-Royce’s power-by-the-hour service. For long, the manufacturing sector has been the subject of much debate about how digital technologies can enable companies to provide advanced services to customers; this transi作者: 同步左右 時間: 2025-3-23 23:07
Entrepreneurial Financerial ventures, including big data startups, require external capital to realize their exponential growth and eventually achieve a successful exit in the form of an initial public offering (IPO) or an acquisition. Therefore, startup founders have to be fully aware of their funding options and potenti作者: Anticoagulants 時間: 2025-3-24 02:31 作者: Visual-Field 時間: 2025-3-24 06:52
Textbook 2023rovides a detailed, yet practical, introduction to the fundamental principles of data science and how entrepreneurs and would-be entrepreneurs can take advantage of it. It walks the reader through sections on data engineering, and data analytics as well as sections on data entrepreneurship and data 作者: 創(chuàng)作 時間: 2025-3-24 13:11 作者: Foolproof 時間: 2025-3-24 17:36
https://doi.org/10.1007/978-981-19-2008-0it explains ., ., and . as the core strategic concepts that are of paramount importance for understanding the digitalization dynamics. The chapter ends with the state-of-the-art insights towards future challenges and avenues for further research.作者: Mumble 時間: 2025-3-24 20:35
2662-2866 applications.Provides discussion questions at the end of eac.The fast-paced technological development and the plethora of data create numerous opportunities waiting to be exploited by entrepreneurs. This book provides a detailed, yet practical, introduction to the fundamental principles of data scie作者: Ambulatory 時間: 2025-3-24 23:14
Data-driven dynamic SEIIR modelerstandable manner. The integration of convolution with deep neural networks is shown to give rise to convolutional neural networks (CNNs). The final part of the chapter presents an example of the application of CNNs to skin cancer detection.作者: 透明 時間: 2025-3-25 06:51 作者: 量被毀壞 時間: 2025-3-25 08:49
Planar and Conforming Arrays of Probess. We discuss the data governance challenges, opportunities, and practices for big data and Internet of Things (IoT) domains. We also present two industrial big data applications/products whose data needs to be governed.作者: 的事物 時間: 2025-3-25 12:46
Some Special Signal-Processing Algorithmson architectures of big data use cases. This chapter is of value for academics, practitioners, and entrepreneurs alike. The analysis of existing reference architectures and success cases will facilitate architecture design, and the selection of most suitable technologies or commercial solutions, when constructing big data systems.作者: 柔美流暢 時間: 2025-3-25 17:32 作者: Brochure 時間: 2025-3-25 23:37 作者: 的闡明 時間: 2025-3-26 02:04
Data Governances. We discuss the data governance challenges, opportunities, and practices for big data and Internet of Things (IoT) domains. We also present two industrial big data applications/products whose data needs to be governed.作者: 配置 時間: 2025-3-26 06:42 作者: 博識 時間: 2025-3-26 10:00 作者: BUCK 時間: 2025-3-26 14:47
Strategy in the Era of Digital Disruptionit explains ., ., and . as the core strategic concepts that are of paramount importance for understanding the digitalization dynamics. The chapter ends with the state-of-the-art insights towards future challenges and avenues for further research.作者: 引起痛苦 時間: 2025-3-26 20:18
Textbook 2023d this book, students of entrepreneurship courses will be better able to commercialize data-driven ideas that may be solutions to real-life problems. Chapters contain detailed examples and cases for a better understanding. Discussion points or questions at the end of each chapter help to deeply reflect on the learning material..作者: 祖?zhèn)髫敭a(chǎn) 時間: 2025-3-26 22:30
Modeling Corrosion and Pitting Problemslly consider the main aspects involving decision-making in data engineering in practice. In addition, we analyze some of the main pros and cons of those decisions to guide the reader during the choice and evaluation of the desired technologies for the problem at hand.作者: 名次后綴 時間: 2025-3-27 05:05
Barker Polynomials and Golay Pairs,nd we introduce the available concepts for the use of DDDM in programmed and nonprogrammed decision-making. We also include a brief description of the link between DDDM and successful data entrepreneurship. We conclude by listing some topics for discussion and further research.作者: Preamble 時間: 2025-3-27 07:03 作者: 友好 時間: 2025-3-27 11:55 作者: 榮幸 時間: 2025-3-27 14:33 作者: SLAG 時間: 2025-3-27 19:15 作者: 角斗士 時間: 2025-3-27 23:43 作者: debunk 時間: 2025-3-28 02:28
Sequential Experimentation and Learningeal-world problems that can be studied as a cMAB problem, and we will review effective solutions to this problem such as the UCB algorithm, Thompson sampling, and bootstrapped Thompson sampling. We focus on application but provide references for readers interested in the underlying theoretical resul作者: VERT 時間: 2025-3-28 06:36 作者: 雇傭兵 時間: 2025-3-28 12:23 作者: convulsion 時間: 2025-3-28 16:12
Entrepreneurial Financeum game, agency problems and diverging incentives cloud the relationship between startup investors and entrepreneurs (Fried and Ganor, New York University Law Review 81:967–1025; 2006). This chapter provides an overview of different types of investors that provide financing for innovative (tech) sta作者: 人類的發(fā)源 時間: 2025-3-28 20:50 作者: 投票 時間: 2025-3-29 03:00
Introduction to network epidemiologyeal-world problems that can be studied as a cMAB problem, and we will review effective solutions to this problem such as the UCB algorithm, Thompson sampling, and bootstrapped Thompson sampling. We focus on application but provide references for readers interested in the underlying theoretical resul作者: 對手 時間: 2025-3-29 03:20
Introduction to computational epidemiologywork data, also bridging between both by analyzing signals on graphs. Besides setting the stage for the important theoretical background and concepts, we outline, in particular, the perspective on industrial applications and provide specific examples of the application of the presented methods in re作者: syring 時間: 2025-3-29 11:10
Indian Statistical Institute Seriesully compete on such digital platforms. The latter is not so easy, given a number of challenges that digital entrepreneurs typically face when being active on such platforms. Finally, we describe the main features of a digital entrepreneurial ecosystem, in which digital entrepreneurs typically opera作者: Orthodontics 時間: 2025-3-29 12:27 作者: 肌肉 時間: 2025-3-29 17:51
Computational Flexible Multibody Dynamics product development process of young firms should be complemented with a customer development process. Before a young firm can grow, customers need to be discovered and built. Later, marketing and sales efforts can be optimized using data collected from the firm’s initial customer base. Modificatio作者: legacy 時間: 2025-3-29 20:30
https://doi.org/10.1007/978-3-031-19554-9Applications of data science in entrepreneurship; Data science for startups; Cyberphysical systems; Dat作者: 疲勞 時間: 2025-3-30 01:08
978-3-031-19556-3Springer Nature Switzerland AG 2023作者: 是突襲 時間: 2025-3-30 05:06
Werner Liebregts,Willem-Jan van den Heuvel,Arjan vOffers a practical approach to leverage big data and AI for new value creation.Compiles detailed examples and cases on data science and its applications.Provides discussion questions at the end of eac作者: 笨拙的你 時間: 2025-3-30 10:18 作者: Pamphlet 時間: 2025-3-30 13:00 作者: Ovulation 時間: 2025-3-30 20:34
J. Zhou,A. M. Kriman,D. K. Ferrytechnique using an inspiring example and discuss how the corresponding algorithms work together with the data engineering pipelines. They provide some guidelines for implementing a classification or regression task for other problems and required materials to evaluate the supervised learning being used.作者: 罵人有污點 時間: 2025-3-30 23:03 作者: Hectic 時間: 2025-3-31 01:00 作者: 愛管閑事 時間: 2025-3-31 05:58 作者: LAIR 時間: 2025-3-31 10:52
Modeling Corrosion and Pitting Problemse from various sources to solve a specific business problem and generate value from it. However, in real-world problems, the time spent preparing the data infrastructure and selecting the right technologies to manage this data tends to be much longer than the time spent on implementing algorithms th作者: 下級 時間: 2025-3-31 14:54
J. Zhou,A. M. Kriman,D. K. Ferrytechnique using an inspiring example and discuss how the corresponding algorithms work together with the data engineering pipelines. They provide some guidelines for implementing a classification or regression task for other problems and required materials to evaluate the supervised learning being u
