LEADER 03027nam 22006971a 450 001 9910953383903321 005 20200514202323.0 010 $a9781350028302 010 $a1350028304 010 $a9781350028326 010 $a1350028320 010 $a9781350028319 010 $a1350028312 024 7 $a10.5040/9781350028326 035 $a(CKB)4340000000270943 035 $a(MiAaPQ)EBC5305753 035 $a(OCoLC)1031368020 035 $a(UkLoBP)bpp09261847 035 $a(MiAaPQ)EBC6162262 035 $a(Au-PeEL)EBL5305753 035 $a(CaPaEBR)ebr11514814 035 $a(OCoLC)1027164548 035 $a(UtOrBLW)bpp09261847 035 $a(UkLoBP)BP9781350028326BC 035 $a(Perlego)804869 035 $a(UtOrBLW)BP9781350028326BC 035 $a(EXLCZ)994340000000270943 100 $a20180531d2018 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aApproaching facial difference $epast and present /$fPatricia Skinner and Emily Cock (eds) 205 $a1st ed. 210 $aLondon $cBloomsbury Academic$d2018 215 $a1 online resource (246 pages) 225 0 $aFacialities: interdisciplinary approaches to the human face 300 $aIncludes index. 311 08$a9781350142978 311 08$a1350142972 311 08$a9781350028296 311 08$a1350028290 320 $aIncludes bibliographical references. 327 $aPart 1: Language--Part 2: Visibility--Part 3: Materiality. 330 $a"What is a face and how does it relate to personhood? Approaching Facial Difference: Past and Present offers an interdisciplinary exploration of the many ways in which faces have been represented in the past and present, focusing on the issue of facial difference and disfigurement read in the light of shifting ideas of beauty and ugliness. Faces are central to all human social interactions, yet their study has been much overlooked by disability scholars and historians of medicine alike. By examining the main linguistic, visual and material approaches to the face from antiquity to contemporary times, contributors place facial diversity at the heart of our historical and cultural narratives. This cutting-edge collection of essays will be an invaluable resource for humanities scholars working across history, literature and visual culture, as well as modern practitioners in education and psychology."--Bloomsbury Publishing. 410 0$aFacialities: Interdisciplinary Approaches to the Human Face 606 $aFace$xDifferentiation 606 $aFace perception 615 0$aFace$xDifferentiation. 615 0$aFace perception. 676 $a153.758 701 $aSkinner$b Patricia$f1965-$0164915 701 $aCock$b Emily$01801847 801 0$bUtOrBLW 801 1$bUtOrBLW 801 2$bUkLoBP 906 $aBOOK 912 $a9910953383903321 996 $aApproaching facial difference$94347246 997 $aUNINA LEADER 03625nam 22005295 450 001 9911039315103321 005 20251101120358.0 010 $a9798868817212$b(electronic bk.) 010 $z9798868817205 024 7 $a10.1007/979-8-8688-1721-2 035 $a(MiAaPQ)EBC32384876 035 $a(Au-PeEL)EBL32384876 035 $a(CKB)41997176400041 035 $a(CaSebORM)9798868817212 035 $a(OCoLC)1548304525 035 $a(OCoLC-P)1548304525 035 $a(DE-He213)979-8-8688-1721-2 035 $a(EXLCZ)9941997176400041 100 $a20251101d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe Data Lakehouse Revolution $eHarnessing the Power of Databricks for Generative AI and Machine Learning /$fby Rajaniesh Kaushikk 205 $a1st ed. 2025. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2025. 215 $a1 online resource (345 pages) 225 1 $aProfessional and Applied Computing Series 311 08$aPrint version: Kaushikk, Rajaniesh The Data Lakehouse Revolution Berkeley, CA : Apress L. P.,c2025 9798868817205 327 $aChapter 1: Getting Started with Databricks -- Chapter 2: Introduction to Machine Learning and Data Lakehouses -- Chapter 3: Data Preparation and Management -- Chapter 4: Building Machine Learning Models -- Chapter 5: AutoML and Model Optimization -- Chapter 6: Deploying Machine Learning Models -- Chapter 7: Advanced Topics in Machine Learning -- Chapter 8: Lakehouse AI and Retrieval-Augmented Generation (RAG) -- Chapter 9: Conclusion and Next Steps. 330 $aWe are racing toward a new kind of AI?faster, smarter, and more connected than ever. At the heart of it is the Data Lakehouse, and Databricks is the engine powering the transformation. Whether you're a data scientist training models, an engineer scaling pipelines, or an architect modernizing your stack, this book gives you what you need to stay ahead. Inside, you'll understand how to unlock the full potential of Machine Learning and Generative AI (GenAI) using Databricks?no fluff, just real tools, real strategies, and real results. From MLFlow and AutoML to Unity Catalog, Retrieval Augment Generation (RAG), and Vector Search, you'll get a complete blueprint for building intelligent systems that actually work in production. With step-by-step labs, industry case studies, and expert tips from someone who's lived through the entire evolution of enterprise AI, this book is your guide to mastering what's next. If you're serious regarding building AI that matters, this is where your journey begins. What You'll Learn Build full-stack ML and GenAI solutions on Databricks Train and track models with MLFlow, AutoML, and tuning strategies Secure and govern data with Unity Catalog Apply explainable, ethical AI techniques Deploy and monitor ML models in real-world pipelines Use RAG and vector search to power GenAI applications Gain confidence with hands-on labs and real enterprise use cases. 410 0$aProfessional and Applied Computing Series 606 $aMicrosoft Azure (Computing platform) 606 $aMachine learning 606 $aArtificial intelligence 615 0$aMicrosoft Azure (Computing platform) 615 0$aMachine learning. 615 0$aArtificial intelligence. 676 $a006.7/6 700 $aKaushikk$b Rajaniesh$01855980 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9911039315103321 996 $aThe Data Lakehouse Revolution$94454472 997 $aUNINA