LEADER 02940nam 2200493 450 001 9910483468203321 005 20210331131924.0 010 $a1-4842-6168-2 024 7 $a10.1007/978-1-4842-6168-2 035 $a(CKB)5460000000008571 035 $a(DE-He213)978-1-4842-6168-2 035 $a(MiAaPQ)EBC6450882 035 $a(CaSebORM)9781484261682 035 $a(PPN)253256461 035 $a(EXLCZ)995460000000008571 100 $a20210331d2021 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aConvolutional neural networks with Swift for Tensorflow $eimage recognition and dataset categorization /$fBrett Koonce 205 $a1st ed. 2021. 210 1$a[Place of publication not identified] :$cApress,$d[2021] 210 4$dİ2021 215 $a1 online resource (XXI, 245 p. 1 illus.) 311 $a1-4842-6167-4 327 $aChapter 1: MNIST: 1D Neural Network -- Chapter 2: MNIST: 2D Neural Network -- Chapter 3: CIFAR: 2D Nueral Network with Blocks -- Chapter 4: VGG Network -- Chapter 5: Resnet 34 -- Chapter 6: Resnet 50 -- Chapter 7: SqueezeNet -- Chapter 8: MobileNrt v1 -- Chapter 9: MobileNet v2 -- Chapter 10: Evolutionary Strategies -- Chapter 11: MobileNet v3 -- Chapter 12: Bag of Tricks -- Chapter 13: MNIST Revisited -- Chapter 14: You are Here. 330 $aDive into and apply practical machine learning and dataset categorization techniques while learning Tensorflow and deep learning. This book uses convolutional neural networks to do image recognition all in the familiar and easy to work with Swift language. It begins with a basic machine learning overview and then ramps up to neural networks and convolutions and how they work. Using Swift and Tensorflow, you'll perform data augmentation, build and train large networks, and build networks for mobile devices. You?ll also cover cloud training and the network you build can categorize greyscale data, such as mnist, to large scale modern approaches that can categorize large datasets, such as imagenet. Convolutional Neural Networks with Swift for Tensorflow uses a simple approach that adds progressive layers of complexity until you have arrived at the current state of the art for this field. You will: Categorize and augment datasets Build and train large networks, including via cloud solutions Deploy complex systems to mobile devices. 606 $aTensorFlow 606 $aNeural networks (Computer science) 606 $aData sets 615 0$aTensorFlow. 615 0$aNeural networks (Computer science) 615 0$aData sets. 676 $a006.32 700 $aKoonce$b Brett$01229657 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483468203321 996 $aConvolutional neural networks with Swift for Tensorflow$92854307 997 $aUNINA LEADER 00818nam0 22002291i 450 001 UON00394741 005 20231205104629.693 100 $a20110627d1938 |0itac50 ba 101 $ager 102 $aDE 105 $a|||| ||||| 200 1 $aAfrikaner erzahlen ihr Leben$fDiedrich Westermann 210 $a[Germania]$cEffener$dc1938 215 $a407 p.$d21 cm 700 1$aWESTERMANN$bDiedrich$3UONV044404$0181446 712 $aEffener$3UONV278286$4650 801 $aIT$bSOL$c20240220$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00394741 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI AFR GEN 0643 $eSI MR 11245 5 0643 996 $aAfrikaner erzahlen ihr Leben$91351352 997 $aUNIOR LEADER 04658nam 22007215 450 001 9910899899303321 005 20241027115927.0 010 $a9783031713712 010 $a3031713710 024 7 $a10.1007/978-3-031-71371-2 035 $a(MiAaPQ)EBC31741958 035 $a(Au-PeEL)EBL31741958 035 $a(CKB)36410322000041 035 $a(DE-He213)978-3-031-71371-2 035 $a(EXLCZ)9936410322000041 100 $a20241027d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence in Accounting and Auditing $eAccessing the Corporate Implications /$fby Mariarita Pierotti, Anna Monreale, Federica De Santis 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Palgrave Macmillan,$d2024. 215 $a1 online resource (249 pages) 311 08$a9783031713705 311 08$a3031713702 320 $aIncludes bibliographical references and index. 327 $a1. The new corporate data ecosystem (Federica De Santis) -- 2. From data to corporate decision-making process (Mariarita Pierotti) -- 3. An introduction to Artificial Intelligence (Anna Monreale) -- 4. The need of Trustworthy Artificial intelligence (Anna Monreale) -- 5. Artificial Intelligence to support Business Decisions (Federica De Santis) -- 6. AI for risk management (Federica De Santis) -- 7. AI for financial accounting (Mariarita Pierotti) -- 8. AI for managerial accounting (Mariarita Pierotti) -- 9. Artificial Intelligence in Auditing (Federica De Santis). 10. Using AI in business context: case studies (Mariarita Pierotti). 330 $aThis book investigates the phenomenon of artificial intelligence (AI) in the accounting world. It integrates accounting competencies with specific competencies in AI and other digital technologies and offers an interdisciplinary perspective. First, the authors review and discuss the literature to summarize and systematize extant research on digitalization in accounting. Second, case studies are included to illustrate the potential impact of AI in business contexts in terms of opportunities and challenges. Based on these, the book explores how digitalization is influencing the accounting practice and what the most important avenues are for future research on digitalization in accounting, and will be of interest to researchers, students, and practitioners of financial technology, accounting, and risk management. Mariarita Pierotti is an Associate Professor in the Computer Science Department at the University of Pisa, Italy. She teaches Fundamentals of Business Management and Financial Analysis and Performance Measurement at the master's degree course in Data science and Business Informatics. Her recent research interests include budget policies, earning management activities, and management control. Anna Monreale is an Associate Professor in the Computer Science Department at the University of Pisa, Italy, and a member of the Knowledge Discovery and Data Mining Laboratory (KDD Lab), a joint research group with the Information Science and Technology Institute of the National Research Council in Pisa. Federica De Santis is an Associate Professor at the University of Pisa, Italy. Her research interests include auditing, management information systems, management accounting, and intellectual capital. She teaches financial accounting, management information systems, and auditing and management control. 606 $aFinancial engineering 606 $aArtificial intelligence 606 $aAccounting 606 $aAuditing 606 $aFinancial risk management 606 $aFinancial Technology and Innovation 606 $aArtificial Intelligence 606 $aAccounting 606 $aFinancial Accounting 606 $aAuditing 606 $aRisk Management 615 0$aFinancial engineering. 615 0$aArtificial intelligence. 615 0$aAccounting. 615 0$aAuditing. 615 0$aFinancial risk management. 615 14$aFinancial Technology and Innovation. 615 24$aArtificial Intelligence. 615 24$aAccounting. 615 24$aFinancial Accounting. 615 24$aAuditing. 615 24$aRisk Management. 676 $a006.3 700 $aPierotti$b Mariarita$0607826 702 $aMonreale$b Anna 702 $aDe Santis$b Federica 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910899899303321 996 $aArtificial Intelligence in Accounting and Auditing$94329753 997 $aUNINA