LEADER 01159nam0 22002891i 450 001 UON00164750 005 20231205103025.696 010 $a09-404-9072-2 100 $a20021121d1990 |0itac50 ba 101 $aeng 102 $aUS 105 $a|||| 1|||| 200 1 $aDiglossia in ancient Hebrew$fGary A. Rendsburg 210 $aNew Haven$cAmerican Oriental Society$d1990 215 $aXXI, 233 p.$d26 cm 410 1$1001UON00065588$12001 $aAmerican oriental series$fEditor Henry M. Hoenigswald$v72 606 $aLingua ebraica$xStudi lessicali$3UONC015301$2FI 620 $aUS$dNew Haven$3UONL000121 686 $aSEB II C$cSTUDI EBRAICI - LINGUISTICA - STUDI SPECIFICI$2A 700 1$aRENDSBURG$bGary A.$3UONV097281$0674628 712 $aAmerican Oriental Society$3UONV246485$4650 801 $aIT$bSOL$c20250613$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00164750 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI SEB II C 043 N $eSI SA 107164 7 043 N 996 $aDiglossia in ancient Hebrew$91283661 997 $aUNIOR LEADER 04994nam 22008055 450 001 9910731486703321 005 20251008164957.0 010 $a9781484295052 010 $a1484295056 024 7 $a10.1007/978-1-4842-9505-2 035 $a(MiAaPQ)EBC30601983 035 $a(Au-PeEL)EBL30601983 035 $a(DE-He213)978-1-4842-9505-2 035 $a(OCoLC)1382689947 035 $a(OCoLC-P)1382689947 035 $a(PPN)272272914 035 $a(CaSebORM)9781484295052 035 $a(CKB)27060361900041 035 $a(Perlego)4515951 035 $a(EXLCZ)9927060361900041 100 $a20230615d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPredicting the Unknown $eThe History and Future of Data Science and Artificial Intelligence /$fby Stylianos Kampakis 205 $a1st ed. 2023. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2023. 215 $a1 online resource (270 pages) 300 $aIncludes index. 311 08$a9781484295045 311 08$a1484295048 327 $a1. Where Are We Now? A Brief History of Uncertainty -- 2. Truth, Logic and the Problem of Induction -- 3. Swans and Space Invaders -- 4. Probability: To Bayes, or not to Bayes? -- 5. What?s Maths Got to Do With It? The Power of Probability Distributions -- 6. Alternative Ideas: Fuzzy Logic and Information Theory -- 7. Statistics: the Oldest Kid on the Block -- 8. Machine Learning: Inside the Black Box -- 9. Causality: Understanding the ?Why? -- 10. Forecasting, and Predicting the Future: The Fox and the Trump -- 11. The Limits of Prediction (Part A): A Futile Pursuit? -- 12. The Limits of Prediction (Part B): Game Theory, Agent-based Modelling and Complexity (Actions and Reactions) -- 13. Uncertainty in Us: How the Human Mind Handles Uncertainty -- 14. Blockchain: Uncertainty in transactions -- 15. Economies of Prediction: A New Industrial Revolution -- Epilogue: The Certainty of Uncertainty. 330 $aAs a society, we?re in a constant struggle to control uncertainty and predict the unknown. Quite often, we think of scientific fields and theories as being separate from each other. But a more careful investigation can uncover the common thread that ties many of those together. From ChatGPT, to Amazon?s Alexa, to Apple?s Siri, data science, and computer science have become part of our lives. In the meantime, the demand for data scientists has grown, as the field has been increasingly called the ?sexiest profession.? This book attempts to specifically cover this gap in literature between data science, machine learning and artificial intelligence (AI). How was uncertainty approached historically, and how has it evolved since? What schools of thought exist in philosophy, mathematics, and engineering, and what role did they play in the development of data science? It uses the history of data science as a stepping stone to explain what the future might hold. Predicting the Unknown provides the framework that will help you understand where AI is headed, and how to best prepare for the world that?s coming in the next few years, both as a society and within a business. It is not technical and avoids equations or technical explanations, yet is written for the intellectually curious reader, and the technical expert interested in the historical details that can help contextualize how we got here. You will: Explore the bigger picture of data science and see how to best anticipate future changes in that field Understand machine learning, AI, and data science Examine data science and AI through engaging historical and human-centric narratives . 606 $aArtificial intelligence 606 $aData structures (Computer science) 606 $aInformation theory 606 $aArtificial intelligence$xData processing 606 $aComputer science 606 $aLogic programming 606 $aMachine learning 606 $aArtificial Intelligence 606 $aData Structures and Information Theory 606 $aData Science 606 $aComputer Science 606 $aLogic in AI 606 $aMachine Learning 615 0$aArtificial intelligence. 615 0$aData structures (Computer science) 615 0$aInformation theory. 615 0$aArtificial intelligence$xData processing. 615 0$aComputer science. 615 0$aLogic programming. 615 0$aMachine learning. 615 14$aArtificial Intelligence. 615 24$aData Structures and Information Theory. 615 24$aData Science. 615 24$aComputer Science. 615 24$aLogic in AI. 615 24$aMachine Learning. 676 $a005.7 700 $aKampakis$b Stylianos$0973114 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910731486703321 996 $aPredicting the Unknown$93394543 997 $aUNINA