LEADER 01154nam0-22003731i-450- 001 990005470870203316 005 20010829120000.0 035 $a000547087 035 $aUSA01000547087 035 $a(ALEPH)000547087USA01 035 $a000547087 100 $a20010829d1984-------|0enac50------ba 101 $aeng 102 $aUS 105 $a|||| ||||| 200 1 $aAdjustment,conditionality , and international financing$fEdited by Joaquin Muns 210 $aWashington$cInternytional Monetary Fund$d1984 215 $a214 p$cill.; 23 cm. 606 $aFinanza internazionale$2FI 620 $dWashington 676 $a332.042$cFinanza internazionale$v21 702 1$aMUNS,$bJoaquin 712 $aInternational Monetary Found 801 $aIT$bSOL$c20120104 912 $a990005470870203316 950 $aDIP.TO SCIENZE ECONOMICHE - (SA)$dDS 300 332.042 MUN$e607 DISES 951 $a300 332.042 MUN$b607 DISES 959 $aBK 969 $aDISES 979 $c20121027$lUSA01$h1532 979 $c20121027$lUSA01$h1613 996 $aAdjustment,conditionality , and international financing$91128293 997 $aUNISA NUM $aUSA7322 LEADER 02992nam 22005775 450 001 9910983305303321 005 20250104115228.0 010 $a9783031759536 010 $a3031759532 024 7 $a10.1007/978-3-031-75953-6 035 $a(CKB)37156144600041 035 $a(MiAaPQ)EBC31874095 035 $a(Au-PeEL)EBL31874095 035 $a(DE-He213)978-3-031-75953-6 035 $a(OCoLC)1484073918 035 $a(EXLCZ)9937156144600041 100 $a20250104d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence for Engineers $eBasics and Implementations /$fby Zhen "Leo" Liu 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (719 pages) 311 08$a9783031759529 311 08$a3031759524 327 $aPreparation Knowledge: Basics of AI -- Tools for Artificial Intelligence -- Linear Models -- Decision Trees -- Support Vector Machine -- Bayesian Algorithms -- Artificial Neural Network -- Deep Learning -- Ensemble Learning -- Clustering -- Dimension Reduction -- Anomaly Detection -- Association Rule Leaming -- Basics of and Value-Based Reinforcement Learning -- Policy-Based Reinforcement Learning. 330 $aThis textbook presents basic knowledge and essential toolsets needed for people who want to step into artificial intelligence (AI). The book is especially suitable for those college students, graduate students, instructors, and IT hobbyists who have an engineering mindset. That is, it serves the idea of getting the job done quickly and neatly with an adequate understanding of why and how. It is designed to allow one to obtain a big picture for both AI and essential AI topics within the shortest amount of time. Designed for a typical undergraduate, graduate, or dual-listed course with a semester-based calendar; Puts theory in context, so readers gain knowledge about the most essential concepts and algorithms; Covers essential terms, algorithms, and useful tools for learning and performing contemporary AI. Extra information is available at AI-engineer.org. 606 $aElectronic circuit design 606 $aComputational intelligence 606 $aMachine learning 606 $aElectronics Design and Verification 606 $aComputational Intelligence 606 $aMachine Learning 615 0$aElectronic circuit design. 615 0$aComputational intelligence. 615 0$aMachine learning. 615 14$aElectronics Design and Verification. 615 24$aComputational Intelligence. 615 24$aMachine Learning. 676 $a621.3815 700 $aLiu$b Zhen (Leo)$0768803 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910983305303321 996 $aArtificial Intelligence for Engineers$94317449 997 $aUNINA