LEADER 03580oam 2200733I 450 001 9910461297203321 005 20200520144314.0 010 $a0-429-89660-3 010 $a0-429-47183-1 010 $a1-283-11861-0 010 $a9786613118615 010 $a1-84940-895-5 024 7 $a10.4324/9780429471834 035 $a(CKB)2670000000093989 035 $a(EBL)709599 035 $a(OCoLC)727649388 035 $a(SSID)ssj0000520919 035 $a(PQKBManifestationID)12175428 035 $a(PQKBTitleCode)TC0000520919 035 $a(PQKBWorkID)10517521 035 $a(PQKB)10847463 035 $a(MiAaPQ)EBC709599 035 $a(Au-PeEL)EBL709599 035 $a(CaPaEBR)ebr10475829 035 $a(CaONFJC)MIL311861 035 $a(OCoLC)1029229579 035 $a(EXLCZ)992670000000093989 100 $a20180706d2018 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAnother kind of evidence $estudies on internalization, annihilation anxiety, and progressive symbolization in the psychoanalytic process /$fNorbert Freedman, Marvin Hurvich, and Rhonda Ward ; with Jesse D. Geller and Joan Hoffenberg 210 1$aAbingdon, Oxon ;$aNew York, NY :$cRoutledge,$d2018. 215 $a1 online resource (381 p.) 225 1 $aCIPS series on the boundaries of psychoanalysis 300 $aDescription based upon print version of record. 311 $a0-367-10705-8 311 $a1-85575-852-0 320 $aIncludes bibliographical references and index. 327 $apt. 1. How therapy lives on -- pt. 2. Three pathways towards the modification of annihilation anxiety -- pt. 3. A specimen of working through. 330 8 $aAnnotation.$bIn the current professional climate, the calls for evidenced-based treatment and the prestige accorded to this emblem, mental health professionals are asking: for what purpose do we seek evidence? For our students? For the public at large? For an inner sense of feeling supported by science? Most disciplines are concerned with cumulative knowledge, aimed toward self-affirmation and self-definition, that is, establishing a sense of legitimacy. The three parts of this volume are directed toward the goal of affirming a public and private sense of the legitimacy of psychoanalysis, thereby shaping professional identity. Each contribution adheres to the precepts of scientific inquiry, with a commitment to affirming or disconfirming clinical propositions, utilizing consensually agreed upon methods of observation, and arriving at inferences that are persuasive and have the potential to move the field forward. Beyond this, each part of this book describes distinct methodologies that generate evidence pertaining to public health policy, the persuasiveness and integrity of our psychoanalytic concepts, and phenomena encountered in daily clinical practice. 410 0$aCIPS series on the boundaries of psychoanalysis. 606 $aPsychoanalysis 606 $aInternalization 606 $aAnxiety 608 $aElectronic books. 615 0$aPsychoanalysis. 615 0$aInternalization. 615 0$aAnxiety. 676 $a150.195 700 $aFreedman$b Norbert$0850378 702 $aGeller$b Jesse D. 702 $aHoffenberg$b Joan 702 $aHurvich$b Marvin 702 $aWard$b Rhonda$cLCSW, 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910461297203321 996 $aAnother kind of evidence$91898722 997 $aUNINA LEADER 01099nam a22002771i 4500 001 991004165869707536 005 20020829073444.0 008 020820s1974 it |||||||||||||||||ita 035 $ab11928025-39ule_inst 035 $aocm00000004$9ExL 040 $aDip.to Filologia Ling. e Lett.$bita$cA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l. 082 04$a398.2045 100 1 $aBarbi, Michele$052609 245 10$aPoesia popolare italiana :$bstudi e proposte /$cMichele Barbi 260 $aFirenze :$bSansoni,$c1974 300 $a166 p. ;$c20 cm 490 0 $aBiblioteca Sansoni 650 4$aCanti popolari italiani 650 4$aPoesia popolare italiana 907 $a.b11928025$b28-04-17$c01-04-03 912 $a991004165869707536 945 $aLE008 Cr F VII 20$g2$i2008000214067$lle008$o-$pE0.00$q-$rl$s- $t0$u3$v0$w3$x0$y.i12199990$z01-04-03 945 $aLE008 FL.M. (TR.P.) I B 20$g1$i2008000367121$lle008$o-$pE0.00$q-$rl$s- $t0$u2$v0$w2$x0$y.i12200001$z01-04-03 996 $aPoesia popolare italiana$9235243 997 $aUNISALENTO 998 $ale008$b01-04-03$cm$da $e-$fita$git $h0$i2 LEADER 02749nam 2200637 450 001 9910786800403321 005 20230803204001.0 010 $a0-8047-9228-3 024 7 $a10.1515/9780804792288 035 $a(CKB)3710000000214100 035 $a(SSID)ssj0001291416 035 $a(PQKBManifestationID)11837148 035 $a(PQKBTitleCode)TC0001291416 035 $a(PQKBWorkID)11246728 035 $a(PQKB)11734382 035 $a(StDuBDS)EDZ0000986025 035 $a(MiAaPQ)EBC1770083 035 $a(DE-B1597)563645 035 $a(DE-B1597)9780804792288 035 $a(Au-PeEL)EBL1770083 035 $a(CaPaEBR)ebr10904655 035 $a(OCoLC)923709228 035 $a(OCoLC)1198929947 035 $a(EXLCZ)993710000000214100 100 $a20140815h20142014 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aPoetic force $epoetry after Kant /$fKevin McLaughlin 210 1$aStanford, California :$cStanford University Press,$d2014. 210 4$d©2014 215 $a1 online resource 225 1 $aMeridian. Crossing Aesthetics 300 $aBibliographic Level Mode of Issuance: Monograph 311 0 $a0-8047-9100-7 320 $aIncludes bibliographical references and index. 327 $tFront matter --$tContents --$tPreface: Poetic Force --$tAcknowledgments --$tTranslations and Abbreviations --$t§1. Ur-ability --$t§2. Hölderlin?s Peace --$t§3. Poetic Reason of State --$t§4. Arnold?s Resignation --$tEpilogue --$tNotes --$tBibliography --$tIndex 330 8 $aThis book argues that the theory of force elaborated in Immanuel Kant's aesthetics is of decisive importance to poetry in the 19th century and to the connection between poetry and philosophy over the last two centuries. Inspired by his deep engagement with the critical theory of Walter Benjamin, who especially developed this Kantian strain of thinking, Kevin McLaughlin uses this theory of force to illuminate the work of three of the most influential 19th century writers in their respective national traditions: Friedrich Ho?lderlin, Charles Baudelaire, and Matthew Arnold. 410 0$aMeridian (Stanford, Calif.) 606 $aPoetry, Modern$y19th century$xHistory and criticism 606 $aAesthetics, Modern$y20th century 606 $aPhilosophy, Modern$y20th century 615 0$aPoetry, Modern$xHistory and criticism. 615 0$aAesthetics, Modern 615 0$aPhilosophy, Modern 676 $a808.1 700 $aMcLaughlin$b Kevin$f1959-$01542674 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910786800403321 996 $aPoetic force$93795592 997 $aUNINA LEADER 03938nam 22005895 450 001 9910427050203321 005 20230412150415.0 010 $a1-4842-5829-0 024 7 $a10.1007/978-1-4842-5829-3 035 $a(CKB)4100000011505216 035 $a(DE-He213)978-1-4842-5829-3 035 $a(MiAaPQ)EBC6371569 035 $a(CaSebORM)9781484258293 035 $a(PPN)252511611 035 $a(EXLCZ)994100000011505216 100 $a20201012d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvanced Analytics in Power BI with R and Python $eIngesting, Transforming, Visualizing /$fby Ryan Wade 205 $a1st ed. 2020. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2020. 215 $a1 online resource (XLVI, 391 p. 84 illus.) 300 $aIncludes index. 311 $a1-4842-5828-2 327 $aPart I. Creating Custom Data Visualizations using R -- 1. The Grammar of Graphics -- 2. Creating R custom visuals in Power BI using ggplot2 -- Part II. Ingesting Data into the Power BI Data Model using R and Python -- 3. Reading CSV Files -- 4. Reading Excel Files -- 5. Reading SQL Server Data -- 6. Reading Data into the Power BI Data Model via an API -- Part III. Transforming Data using R and Python.-7. Advanced String Manipulation and Pattern Matching -- 8. Calculated Columns using R and Python -- Part IV. Machine Learning & AI in Power BI using R and Python -- 9. Applying Machine Learning and AI to your Power BI Data Models -- 10. Productionizing Data Science Models and Data Wrangling Scripts. . 330 $aThis easy-to-follow guide provides R and Python recipes to help you learn and apply the top languages in the field of data analytics to your work in Microsoft Power BI. Data analytics expert and author Ryan Wade shows you how to use R and Python to perform tasks that are extremely hard to do, if not impossible, using native Power BI tools without Power BI Premium capacity. For example, you will learn to score Power BI data using custom data science models, including powerful models from Microsoft Cognitive Services. The R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration, but become easier through the application of data wrangling features that languages such as R and Python support. If you are a BI developer, business analyst, data analyst, or a data scientist who wants to push Power BI and transform it from being just a business intelligence tool into an advanced data analytics tool, then this is the book to help you to do that. You will: Create advanced data visualizations through R using the ggplot2 package Ingest data using R and Python to overcome the limitations of Power Query Apply machine learning models to your data using R and Python Incorporate advanced AI in Power BI via Microsoft Cognitive Services, IBM Watson, and pre-trained models in SQL Server Machine Learning Services Perform string manipulations not otherwise possible in Power BI using R and Python. 606 $aMicrosoft software 606 $aMicrosoft .NET Framework 606 $aQuantitative research 606 $aBig data 606 $aMicrosoft 606 $aData Analysis and Big Data 606 $aBig Data 615 0$aMicrosoft software. 615 0$aMicrosoft .NET Framework. 615 0$aQuantitative research. 615 0$aBig data. 615 14$aMicrosoft. 615 24$aData Analysis and Big Data. 615 24$aBig Data. 676 $a001.4226028566 700 $aWade$b Ryan$0859869 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910427050203321 996 $aAdvanced analytics in power BI with R and Python$91918799 997 $aUNINA