Artificial intelligence in business management:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Singapore
Springer
[2023]
|
| Ausgabe: | 1st ed. |
| Schriftenreihe: | Machine Learning: Foundations, Methodologies, and Applications
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | xiii, 383 Seiten Illustrationen |
| ISBN: | 9789819945573 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV049046132 | ||
| 003 | DE-604 | ||
| 005 | 20240308 | ||
| 007 | t| | ||
| 008 | 230712s2023 xx a||| |||| 00||| eng d | ||
| 020 | |a 9789819945573 |9 978-981-99-4557-3 | ||
| 035 | |a (OCoLC)1422374702 | ||
| 035 | |a (DE-599)BVBBV049046132 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-1102 |a DE-384 | ||
| 084 | |a ST 300 |0 (DE-625)143650: |2 rvk | ||
| 100 | 1 | |a Teoh, Teik Toe |e Verfasser |0 (DE-588)1258726793 |4 aut | |
| 245 | 1 | 0 | |a Artificial intelligence in business management |c Teik Toe Teoh, Yu Jin Goh |
| 250 | |a 1st ed. | ||
| 264 | 1 | |a Singapore |b Springer |c [2023] | |
| 300 | |a xiii, 383 Seiten |b Illustrationen | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Machine Learning: Foundations, Methodologies, and Applications | |
| 650 | 0 | 7 | |a Management |0 (DE-588)4037278-9 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Künstliche Intelligenz |0 (DE-588)4033447-8 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Künstliche Intelligenz |0 (DE-588)4033447-8 |D s |
| 689 | 0 | 1 | |a Management |0 (DE-588)4037278-9 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Goh, Yun Jin |e Verfasser |4 aut | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-981-99-4558-0 |
| 856 | 4 | 2 | |m Digitalisierung UB Augsburg - ADAM Catalogue Enrichment |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034308577&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 856 | 4 | 2 | |m Digitalisierung UB Augsburg - ADAM Catalogue Enrichment |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034308577&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |3 Klappentext |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-034308577 | |
Datensatz im Suchindex
| _version_ | 1815529339563802624 |
|---|---|
| adam_text |
Part I Artificial Intelligence Algorithms 1 Introduction to Artificial Intelligence. 1.1 Introduction. 1.2 History of Artificial Intelligence. 1.3 Types of Artificial Intelligence Algorithms. 1.4 Organization of the Book. References. 3 3 6 6 7 8 2 Regression . 2.1 Linear Regression. 2.2 Decision Tree Regression. 2.3 Random Forests. 2.4 Neural Network. 2.5 Improving Regression Performance. 2.5.1 Boxplot. 2.5.2 Remove Outlier. 2.5.3 Remove NA. 2.5.4 Feature
Importance. Exercises. References. 9 13 15 17 19 21 21 23 25 25 27 28 3 Classification. 3.1 Logistic Regression. 3.2 Decision Tree and Random Forest. 3.3 Neural Network. 3.4 Support Vector Machines. 3.4.1 Important Hyperparameters. 3.5 Naive Bayes . 3.6 Improving Classification Performance. Exercises. References. 29 34 38 40 43 44 46 47 54 55
Clustering . 4.1 Introduction to Clustering. 4.2 K-means. 4.3 The Elbow Method. Exercises. References. 57 57 57 59 62 63 Time Series. 5.1 Introduction to Time Series. 5.2 Stationarity . 5.3 Level, Trend, and Seasonality. 5.4 Exponential Smoothing. 5.4.1 Simple Exponential Smoothing. 5.4.2 Double Exponential Smoothing (Holt’s Exponential Smoothing) . 73 5.4.3 Triple Exponential Smoothing (Holt-Winters Exponential Smoothing) . 75 5.5 Moving Average Smoothing. 5.6
Autoregression. 5.7 Moving Average Process. 5.8 S ARIMA. 5.9 ARCH/GARCH. Exercises. References. 65 65 67 68 72 72 76 77 78 80 81 84 84 Convolutional Neural Networks. 87 6.1 The Convolution Operation. 88 6.2 Pooling. 89 6.3 Flattening. 91 6.4 Building a CNN. 91 6.5 CNN Architectures. 95 6.5.1 VGG16. 95 6.5.2 InceptionNet. 96 6.5.3 ResNet. 96 6.6
Finetuning. 97 6.7 Other Tasks That Use CNNs. 99 6.7.1 Object Detection. 99 6.7.2 Semantic Segmentation . . . 100 Exercises. 100 References. 102 Text Mining. 7.1 Preparing the Data. 7.2 Texts for Classification. 7.3 Vectorize. 7.4 TF-IDF. 103 103 106 107 110
8 7.5 Web Scraping. 7.6 Tokenization. 7.7 Part of Speech Tagging. 7.8 Stemming and . Exercises . Reference. 113 113 113 114 115 116 Chatbot, Speech, and NLP. 8.1 Speech to Text. 8.2 Preparing the Data for Chatbot. 8.2.1 Download the Data. 8.2.2 Reading the Data from the Files. 8.2.3 Preparing Data for Seq2Seq Model. 8.3 Defining the Encoder-Decoder Model. 8.4 Training the Model. 8.5 Defining Inference Models. 8.6 Talking with Our Chatbot.
Exercises. References. 117 117 120 120 120 121 123 125 128 129 131 131 Partll Applications of Artificial Intelligence in Business Management 9 AI in Human Resource Management. 9.1 Introduction to Human Resource Management. 9.2 Artificial Intelligence in Human Resources. 9.3 Applications of AI in Human Resources. 9.3.1 Salary Prediction. 9.3.2 Recruitment. 9.3.3 Course Recommendation. 9.3.4 Employee Attrition Prediction. Exercises. References. 135 135 137 138 138 149 156 163 172 173 10 AI in Sales. 10.1 Introduction to Sales. 10.1.1 The Sales Cycle. 10.2
Artificial Intelligence in Sales. 10.3 Applications of AI in Sales. 10.3.1 Lead Scoring. 10.3.2 Sales Assistant Chatbot. 10.3.3 Product Recommender Systems. 10.3.4 Recommending via Pairwise Correlated Purchases. Exercises. References. 175 175 176 178 179 179 188 195 201 207 208
11 AI in Marketing. 11.1 Introduction to Marketing. 11.1.1 Sales vs Marketing . 11.2 Artificial Intelligence in Marketing. 11.3 Applications of AI in Marketing. 11.3.1 Customer Segmentation. 11.3.2 Analyzing Brand Associations. Exercises . References. 209 209 211 211 212 212 219 222 223 12 AI in Supply Chain Management. 12.1 Introduction to Supply Chain Management . 12.1.1 Supply Chain Definition . 12.1.2 Types of Supply Chain Models. 12.1.3 Bullwhip Effect. 12.1.4 Causes of Variation in Orders. 12.1.5 Reducing the Bullwhip Effect. 12.2 Artificial Intelligence in Supply Chain Management. 12.3 Applications of AI in
Supply Chain Management. 12.3.1 Demand Forecasting with AnomalyDetection. 12.3.2 Quality Assurance. 12.3.3 Estimating Delivery Time. 12.3.4 Delivery Optimization. Exercises. References. 225 225 225 227 228 229 229 231 233 233 239 245 249 254 255 13 AI in Operations Management . 13.1 Introduction to Operations Management. 13.1.1 Business Process Management. 13.1.2 Six Sigma. 13.1.3 Supply Chain Management (SCM) vs. Operations Management (OM). 13.2 Artificial Intelligence in Operations Management. 13.3 Applications of AI in Operations. 13.3.1 Root Cause Analysis for IT Operations. 13.3.2 Predictive Maintenance. 13.3.3 Process Automation.
Exercises. References. . 257 257 258 259 AI in Corporate Finance. 14.1 Introduction to Corporate Finance. 14.2 Artificial Intelligence in Finance. 14.3 Applications of AI in Corporate Finance. 14.3.1 Default Prediction.,. 14.3.2 Predicting Credit Card Fraud. 283 283 284 285 285 294 14 259 261 262 262 267 271 282 282
Exercises . 302 References. 302 15 AI in Business Law. 15.1 Introduction to Business Law. 15.1.1 Types of Businesses. 15.1.2 Types of Business Laws. 15.2 Artificial Intelligence in Business Law. 15.3 Applications of AI in Business Law. 15.3.1 Legal Document Summarization. 15.3.2 Contract Review Assistant. 15.3.3 Legal Research Assistant. Exercises . References. 305 305 306 308 309 311 311 315 324 334 335 16 AI in Business Strategy. 16.1 Introduction to Business Strategy. 16.1.1 Types of Business Strategies. 16.1.2 Business
Strategy Frameworks . 16.1.3 Barriers to Entry. 16.2 Artificial Intelligence in Business Strategy. 16.3 Applications of AI in Business Strategy. 16.3.1 Startup Acquisition. 16.3.2 Identifying Closest Competitors. 16.3.3 SWOT Analysis. Exercises. References. 337 337 337 339 343 344 345 345 353 367 377 377 Index. 379
Artificial intelligence (AI) is rapidly gaining significance in the business world. With more and more organizations adopt AI technologies, there is a growing demand for business leaders, managers, and practitioners who can harness Al’s potential to improve operations, increase efficiency, and drive innovation. This book aims to help management professionals exploit the predictive powers of AI and demonstrate to AI practitioners how to apply their expertise in fundamental business operations. It showcases how AI technology innovations can enhance various aspects of business management, such as business strategy, finance, and marketing. Readers interested in AI for business management will find several topics of particular interest, including how AI can improve decision-making in business strategy, streamline operational processes, and enhance customer satisfaction. As AI becomes an increasingly important tool in the business world, this book offers valuable insights into how it can be applied to various industries and business settings. Through this book, readers will gain a better understanding of how AI can be applied to improve business management practices and practical guidance on how to implement AI projects in a business context. This book also provides practical guides on how to implement AI projects in a business context using Python programming. By reading this book, readers will be better equipped to make informed decisions about how to leverage AI for business success. |
| adam_txt |
Part I Artificial Intelligence Algorithms 1 Introduction to Artificial Intelligence. 1.1 Introduction. 1.2 History of Artificial Intelligence. 1.3 Types of Artificial Intelligence Algorithms. 1.4 Organization of the Book. References. 3 3 6 6 7 8 2 Regression . 2.1 Linear Regression. 2.2 Decision Tree Regression. 2.3 Random Forests. 2.4 Neural Network. 2.5 Improving Regression Performance. 2.5.1 Boxplot. 2.5.2 Remove Outlier. 2.5.3 Remove NA. 2.5.4 Feature
Importance. Exercises. References. 9 13 15 17 19 21 21 23 25 25 27 28 3 Classification. 3.1 Logistic Regression. 3.2 Decision Tree and Random Forest. 3.3 Neural Network. 3.4 Support Vector Machines. 3.4.1 Important Hyperparameters. 3.5 Naive Bayes . 3.6 Improving Classification Performance. Exercises. References. 29 34 38 40 43 44 46 47 54 55
Clustering . 4.1 Introduction to Clustering. 4.2 K-means. 4.3 The Elbow Method. Exercises. References. 57 57 57 59 62 63 Time Series. 5.1 Introduction to Time Series. 5.2 Stationarity . 5.3 Level, Trend, and Seasonality. 5.4 Exponential Smoothing. 5.4.1 Simple Exponential Smoothing. 5.4.2 Double Exponential Smoothing (Holt’s Exponential Smoothing) . 73 5.4.3 Triple Exponential Smoothing (Holt-Winters Exponential Smoothing) . 75 5.5 Moving Average Smoothing. 5.6
Autoregression. 5.7 Moving Average Process. 5.8 S ARIMA. 5.9 ARCH/GARCH. Exercises. References. 65 65 67 68 72 72 76 77 78 80 81 84 84 Convolutional Neural Networks. 87 6.1 The Convolution Operation. 88 6.2 Pooling. 89 6.3 Flattening. 91 6.4 Building a CNN. 91 6.5 CNN Architectures. 95 6.5.1 VGG16. 95 6.5.2 InceptionNet. 96 6.5.3 ResNet. 96 6.6
Finetuning. 97 6.7 Other Tasks That Use CNNs. 99 6.7.1 Object Detection. 99 6.7.2 Semantic Segmentation . . . 100 Exercises. 100 References. 102 Text Mining. 7.1 Preparing the Data. 7.2 Texts for Classification. 7.3 Vectorize. 7.4 TF-IDF. 103 103 106 107 110
8 7.5 Web Scraping. 7.6 Tokenization. 7.7 Part of Speech Tagging. 7.8 Stemming and . Exercises . Reference. 113 113 113 114 115 116 Chatbot, Speech, and NLP. 8.1 Speech to Text. 8.2 Preparing the Data for Chatbot. 8.2.1 Download the Data. 8.2.2 Reading the Data from the Files. 8.2.3 Preparing Data for Seq2Seq Model. 8.3 Defining the Encoder-Decoder Model. 8.4 Training the Model. 8.5 Defining Inference Models. 8.6 Talking with Our Chatbot.
Exercises. References. 117 117 120 120 120 121 123 125 128 129 131 131 Partll Applications of Artificial Intelligence in Business Management 9 AI in Human Resource Management. 9.1 Introduction to Human Resource Management. 9.2 Artificial Intelligence in Human Resources. 9.3 Applications of AI in Human Resources. 9.3.1 Salary Prediction. 9.3.2 Recruitment. 9.3.3 Course Recommendation. 9.3.4 Employee Attrition Prediction. Exercises. References. 135 135 137 138 138 149 156 163 172 173 10 AI in Sales. 10.1 Introduction to Sales. 10.1.1 The Sales Cycle. 10.2
Artificial Intelligence in Sales. 10.3 Applications of AI in Sales. 10.3.1 Lead Scoring. 10.3.2 Sales Assistant Chatbot. 10.3.3 Product Recommender Systems. 10.3.4 Recommending via Pairwise Correlated Purchases. Exercises. References. 175 175 176 178 179 179 188 195 201 207 208
11 AI in Marketing. 11.1 Introduction to Marketing. 11.1.1 Sales vs Marketing . 11.2 Artificial Intelligence in Marketing. 11.3 Applications of AI in Marketing. 11.3.1 Customer Segmentation. 11.3.2 Analyzing Brand Associations. Exercises . References. 209 209 211 211 212 212 219 222 223 12 AI in Supply Chain Management. 12.1 Introduction to Supply Chain Management . 12.1.1 Supply Chain Definition . 12.1.2 Types of Supply Chain Models. 12.1.3 Bullwhip Effect. 12.1.4 Causes of Variation in Orders. 12.1.5 Reducing the Bullwhip Effect. 12.2 Artificial Intelligence in Supply Chain Management. 12.3 Applications of AI in
Supply Chain Management. 12.3.1 Demand Forecasting with AnomalyDetection. 12.3.2 Quality Assurance. 12.3.3 Estimating Delivery Time. 12.3.4 Delivery Optimization. Exercises. References. 225 225 225 227 228 229 229 231 233 233 239 245 249 254 255 13 AI in Operations Management . 13.1 Introduction to Operations Management. 13.1.1 Business Process Management. 13.1.2 Six Sigma. 13.1.3 Supply Chain Management (SCM) vs. Operations Management (OM). 13.2 Artificial Intelligence in Operations Management. 13.3 Applications of AI in Operations. 13.3.1 Root Cause Analysis for IT Operations. 13.3.2 Predictive Maintenance. 13.3.3 Process Automation.
Exercises. References. . 257 257 258 259 AI in Corporate Finance. 14.1 Introduction to Corporate Finance. 14.2 Artificial Intelligence in Finance. 14.3 Applications of AI in Corporate Finance. 14.3.1 Default Prediction.,. 14.3.2 Predicting Credit Card Fraud. 283 283 284 285 285 294 14 259 261 262 262 267 271 282 282
Exercises . 302 References. 302 15 AI in Business Law. 15.1 Introduction to Business Law. 15.1.1 Types of Businesses. 15.1.2 Types of Business Laws. 15.2 Artificial Intelligence in Business Law. 15.3 Applications of AI in Business Law. 15.3.1 Legal Document Summarization. 15.3.2 Contract Review Assistant. 15.3.3 Legal Research Assistant. Exercises . References. 305 305 306 308 309 311 311 315 324 334 335 16 AI in Business Strategy. 16.1 Introduction to Business Strategy. 16.1.1 Types of Business Strategies. 16.1.2 Business
Strategy Frameworks . 16.1.3 Barriers to Entry. 16.2 Artificial Intelligence in Business Strategy. 16.3 Applications of AI in Business Strategy. 16.3.1 Startup Acquisition. 16.3.2 Identifying Closest Competitors. 16.3.3 SWOT Analysis. Exercises. References. 337 337 337 339 343 344 345 345 353 367 377 377 Index. 379
Artificial intelligence (AI) is rapidly gaining significance in the business world. With more and more organizations adopt AI technologies, there is a growing demand for business leaders, managers, and practitioners who can harness Al’s potential to improve operations, increase efficiency, and drive innovation. This book aims to help management professionals exploit the predictive powers of AI and demonstrate to AI practitioners how to apply their expertise in fundamental business operations. It showcases how AI technology innovations can enhance various aspects of business management, such as business strategy, finance, and marketing. Readers interested in AI for business management will find several topics of particular interest, including how AI can improve decision-making in business strategy, streamline operational processes, and enhance customer satisfaction. As AI becomes an increasingly important tool in the business world, this book offers valuable insights into how it can be applied to various industries and business settings. Through this book, readers will gain a better understanding of how AI can be applied to improve business management practices and practical guidance on how to implement AI projects in a business context. This book also provides practical guides on how to implement AI projects in a business context using Python programming. By reading this book, readers will be better equipped to make informed decisions about how to leverage AI for business success. |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Teoh, Teik Toe Goh, Yun Jin |
| author_GND | (DE-588)1258726793 |
| author_facet | Teoh, Teik Toe Goh, Yun Jin |
| author_role | aut aut |
| author_sort | Teoh, Teik Toe |
| author_variant | t t t tt ttt y j g yj yjg |
| building | Verbundindex |
| bvnumber | BV049046132 |
| classification_rvk | ST 300 |
| ctrlnum | (OCoLC)1422374702 (DE-599)BVBBV049046132 |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| edition | 1st ed. |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000 c 4500</leader><controlfield tag="001">BV049046132</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20240308</controlfield><controlfield tag="007">t|</controlfield><controlfield tag="008">230712s2023 xx a||| |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9789819945573</subfield><subfield code="9">978-981-99-4557-3</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1422374702</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV049046132</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-1102</subfield><subfield code="a">DE-384</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 300</subfield><subfield code="0">(DE-625)143650:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Teoh, Teik Toe</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1258726793</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Artificial intelligence in business management</subfield><subfield code="c">Teik Toe Teoh, Yu Jin Goh</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st ed.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Singapore</subfield><subfield code="b">Springer</subfield><subfield code="c">[2023]</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">xiii, 383 Seiten</subfield><subfield code="b">Illustrationen</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Machine Learning: Foundations, Methodologies, and Applications</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Management</subfield><subfield code="0">(DE-588)4037278-9</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Künstliche Intelligenz</subfield><subfield code="0">(DE-588)4033447-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Künstliche Intelligenz</subfield><subfield code="0">(DE-588)4033447-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Management</subfield><subfield code="0">(DE-588)4037278-9</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Goh, Yun Jin</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Online-Ausgabe</subfield><subfield code="z">978-981-99-4558-0</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">Digitalisierung UB Augsburg - ADAM Catalogue Enrichment</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034308577&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">Digitalisierung UB Augsburg - ADAM Catalogue Enrichment</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034308577&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Klappentext</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034308577</subfield></datafield></record></collection> |
| id | DE-604.BV049046132 |
| illustrated | Illustrated |
| index_date | 2024-07-03T22:20:22Z |
| indexdate | 2024-11-12T15:01:41Z |
| institution | BVB |
| isbn | 9789819945573 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034308577 |
| oclc_num | 1422374702 |
| open_access_boolean | |
| owner | DE-1102 DE-384 |
| owner_facet | DE-1102 DE-384 |
| physical | xiii, 383 Seiten Illustrationen |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | Springer |
| record_format | marc |
| series2 | Machine Learning: Foundations, Methodologies, and Applications |
| spelling | Teoh, Teik Toe Verfasser (DE-588)1258726793 aut Artificial intelligence in business management Teik Toe Teoh, Yu Jin Goh 1st ed. Singapore Springer [2023] xiii, 383 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Machine Learning: Foundations, Methodologies, and Applications Management (DE-588)4037278-9 gnd rswk-swf Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Künstliche Intelligenz (DE-588)4033447-8 s Management (DE-588)4037278-9 s DE-604 Goh, Yun Jin Verfasser aut Erscheint auch als Online-Ausgabe 978-981-99-4558-0 Digitalisierung UB Augsburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034308577&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Augsburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034308577&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Teoh, Teik Toe Goh, Yun Jin Artificial intelligence in business management Management (DE-588)4037278-9 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| subject_GND | (DE-588)4037278-9 (DE-588)4033447-8 |
| title | Artificial intelligence in business management |
| title_auth | Artificial intelligence in business management |
| title_exact_search | Artificial intelligence in business management |
| title_exact_search_txtP | Artificial intelligence in business management |
| title_full | Artificial intelligence in business management Teik Toe Teoh, Yu Jin Goh |
| title_fullStr | Artificial intelligence in business management Teik Toe Teoh, Yu Jin Goh |
| title_full_unstemmed | Artificial intelligence in business management Teik Toe Teoh, Yu Jin Goh |
| title_short | Artificial intelligence in business management |
| title_sort | artificial intelligence in business management |
| topic | Management (DE-588)4037278-9 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| topic_facet | Management Künstliche Intelligenz |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034308577&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034308577&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT teohteiktoe artificialintelligenceinbusinessmanagement AT gohyunjin artificialintelligenceinbusinessmanagement |