標(biāo)題: Titlebook: Deploying AI in the Enterprise; IT Approaches for De Eberhard Hechler,Martin Oberhofer,Thomas Schaeck Book 2020 Eberhard Hechler, Martin Ob [打印本頁] 作者: VERSE 時間: 2025-3-21 20:06
書目名稱Deploying AI in the Enterprise影響因子(影響力)
書目名稱Deploying AI in the Enterprise影響因子(影響力)學(xué)科排名
書目名稱Deploying AI in the Enterprise網(wǎng)絡(luò)公開度
書目名稱Deploying AI in the Enterprise網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Deploying AI in the Enterprise被引頻次
書目名稱Deploying AI in the Enterprise被引頻次學(xué)科排名
書目名稱Deploying AI in the Enterprise年度引用
書目名稱Deploying AI in the Enterprise年度引用學(xué)科排名
書目名稱Deploying AI in the Enterprise讀者反饋
書目名稱Deploying AI in the Enterprise讀者反饋學(xué)科排名
作者: Biofeedback 時間: 2025-3-21 20:25 作者: seruting 時間: 2025-3-22 03:35 作者: inscribe 時間: 2025-3-22 07:38
AI and Quantum Computingd be built (which he believed to be the case) or if classical computers can simulate the probabilistic behavior of a true quantum system (which he answered with a clear no). This research paper sparked interest in the scientific research community, which started to seriously explore whether or not a quantum computer can actually be built.作者: atopic 時間: 2025-3-22 08:53
In Summary and Onwardal enterprise aspects, such as . challenges, AI in the context of ., ., ., and .. We have also exposed you to some limitations of AI?– including limitations that may persist for the foreseeable future?– and some exciting and emerging topics, such as AI in the context of . and ..作者: Prosaic 時間: 2025-3-22 16:43 作者: Prosaic 時間: 2025-3-22 21:05 作者: MORT 時間: 2025-3-22 23:29 作者: A精確的 時間: 2025-3-23 01:50 作者: 吝嗇性 時間: 2025-3-23 05:52 作者: 愛國者 時間: 2025-3-23 13:02 作者: 愛花花兒憤怒 時間: 2025-3-23 16:08
actices on how to successfully deploy sustainable AI solutioYour company has committed to AI. Congratulations, now what? This practical book offers a holistic plan for implementing AI from the perspective of IT and IT operations in the enterprise. You will learn about AI’s capabilities, potential, l作者: Offbeat 時間: 2025-3-23 20:21 作者: Iatrogenic 時間: 2025-3-23 23:03 作者: Anthem 時間: 2025-3-24 03:01 作者: 建筑師 時間: 2025-3-24 09:20 作者: Inculcate 時間: 2025-3-24 14:33 作者: ADORE 時間: 2025-3-24 16:50 作者: 藐視 時間: 2025-3-24 19:50
https://doi.org/10.1007/978-1-4842-6206-1AI; AI and Blockchain; AI and Quantum Programming; Artificial Intelligence in IT; Artificial Intelligenc作者: SHOCK 時間: 2025-3-25 00:10 作者: 否決 時間: 2025-3-25 06:03 作者: Hyperopia 時間: 2025-3-25 11:03 作者: 禮節(jié) 時間: 2025-3-25 14:37
AI and Change ManagementChange is usually perceived as a threat, causing uncertainty, sentiments, and risks to organizations and individuals alike. However, change comes along with new business and personal opportunities. AI has the potential to accelerate and improve change management and make it more unerringly and human-centric.作者: prostatitis 時間: 2025-3-25 15:52
AI and Blockchainver, the key idea is actually 17 years older. The first mentioning of key blockchain concepts goes back to 1991 when Stuart Haber and Scott Stornetta described the concept of a cryptographically secured chain of blocks for the first time.作者: 動機 時間: 2025-3-25 23:45 作者: 發(fā)展 時間: 2025-3-26 01:01 作者: 冰河期 時間: 2025-3-26 04:33 作者: Coordinate 時間: 2025-3-26 12:20
https://doi.org/10.1007/978-3-658-44913-1Architecture building blocks作者: 飛鏢 時間: 2025-3-26 13:53 作者: Sad570 時間: 2025-3-26 16:47 作者: GRAVE 時間: 2025-3-26 23:06 作者: Yag-Capsulotomy 時間: 2025-3-27 04:01
https://doi.org/10.57088/978-3-7329-8885-3imization (DO). We don’t go into the details on the 101 of these concepts or mathematical and statistical science behind these areas; instead, we are discussing considerations about their practical application in enterprises or other organizations. It should serve as a high-level introduction for re作者: 懦夫 時間: 2025-3-27 06:29 作者: 因無茶而冷淡 時間: 2025-3-27 09:25 作者: 豪華 時間: 2025-3-27 15:53 作者: antiquated 時間: 2025-3-27 21:14 作者: GEN 時間: 2025-3-27 23:03 作者: Cupping 時間: 2025-3-28 06:10 作者: GILD 時間: 2025-3-28 09:49 作者: headway 時間: 2025-3-28 13:32 作者: 獨白 時間: 2025-3-28 16:38 作者: 有角 時間: 2025-3-28 19:44 作者: 倔強一點 時間: 2025-3-28 23:07
https://doi.org/10.1007/978-3-658-44913-1 AI, the . to get from data to predictions to optimal decisions and actions, and important . and . aspects. We have furthermore elaborated on additional enterprise aspects, such as . challenges, AI in the context of ., ., ., and .. We have also exposed you to some limitations of AI?– including limit作者: 縫紉 時間: 2025-3-29 06:07 作者: Obstruction 時間: 2025-3-29 10:07 作者: 向外才掩飾 時間: 2025-3-29 11:40
Schlussbemerkungen: Treibgut und StrandgutChange is usually perceived as a threat, causing uncertainty, sentiments, and risks to organizations and individuals alike. However, change comes along with new business and personal opportunities. AI has the potential to accelerate and improve change management and make it more unerringly and human-centric.作者: 長處 時間: 2025-3-29 17:57 作者: tinnitus 時間: 2025-3-29 20:45 作者: FLOUR 時間: 2025-3-30 01:04
Book 2020cture, and its role in enabling successful and sustainable AI deployments.And you will come away with an understanding of how to effectively leverage AI to augment usage of core information in Master Data Management (MDM) solutions..What You Will Learn.Understand the most important AI concepts, incl作者: 改正 時間: 2025-3-30 08:02 作者: Infuriate 時間: 2025-3-30 10:13 作者: anesthesia 時間: 2025-3-30 14:46
AI Information Architecturen introduction into this topic, we briefly review key aspects of an information architecture (IA) and highlight the logical and physical IA components in the context of AI. These are important to the reader in order to fully understand the impact of AI on an existing information architecture. Any ar作者: Tincture 時間: 2025-3-30 18:51
From Data to Predictions to Optimal Actionso solve real business problems. Decision optimization (DO) takes predictive insight one step further and guarantees that an optimal combination of business-relevant actions can be taken based on predictive insight with relevant context.作者: modifier 時間: 2025-3-30 21:29 作者: 駭人 時間: 2025-3-31 02:41 作者: reaching 時間: 2025-3-31 07:48
AI and Governanceecting our societies. Inference of predictive and ML-driven insight into business processes can be characterized by a great deal of autonomous decision making, which may be perceived by some users as incomprehensible or elusive. Since AI-based decision making ought to be meaningful and human compreh
