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Cours 1 du module "Piloter un projet informatique en bibliothèque". Formation initiale des élèves conservateurs territoriaux de bibliothèques - INET
L'écosystème informatique en bibliothèque : le SIGB
L'écosystème informatique en bibliothèque : le SIGB
Virginie Delaine
강현우, 권서현, 김지오, 박민지, 황다연
21-2 에어비앤비 리뷰평점 EDA 1팀
21-2 에어비앤비 리뷰평점 EDA 1팀
DataScienceLab
This developer-focused webinar will explain how to use the Cypher graph query language. Cypher, a query language designed specifically for graphs, allows for expressing complex graph patterns using simple ASCII art-like notation and offers a simple but expressive approach for working with graph data. During this webinar you'll learn: -Basic Cypher syntax -How to construct graph patterns using Cypher -Querying existing data -Data import with Cypher -Using aggregations such as statistical functions -Extending the power of Cypher using procedures and functions
Intro to Cypher
Intro to Cypher
Neo4j
6기 EDA 프로젝트 5조(김도언, 박세승, 박수빈, 박준우, 이승재)
Airbnb 리뷰데이터 분석을 통한 좋은 숙소의 조건 분석
Airbnb 리뷰데이터 분석을 통한 좋은 숙소의 조건 분석
DataScienceLab
The journey - ANN to Generative AI
Generative AI and Security (1).pptx.pdf
Generative AI and Security (1).pptx.pdf
Priyanka Aash
For companies that solve real-world problems and generate revenue from the data science products, being able to understand why a model makes a certain prediction can be as crucial as achieving high prediction accuracy in many applications. However, as data scientists pursuing higher accuracy by implementing complex algorithms such as ensemble or deep learning models, the algorithm itself becomes a blackbox and it creates the trade-off between accuracy and interpretability of a model’s output. To address this problem, a unified framework SHAP (SHapley Additive exPlanations) was developed to help users interpret the predictions of complex models. In this session, we will talk about how to apply SHAP to various modeling approaches (GLM, XGBoost, CNN) to explain how each feature contributes and extract intuitive insights from a particular prediction. This talk is intended to introduce the concept of general purpose model explainer, as well as help practitioners understand SHAP and its applications.
Unified Approach to Interpret Machine Learning Model: SHAP + LIME
Unified Approach to Interpret Machine Learning Model: SHAP + LIME
Databricks
6기 EDA 프로젝트 1조(강현우, 권서현, 김지오, 박민지, 황다연)
에어비앤비 리뷰데이터 분석을 통한 지역별 호스트 전략 제언
에어비앤비 리뷰데이터 분석을 통한 지역별 호스트 전략 제언
DataScienceLab
Modeling the Doppler Effect using Audacity. Can we model the Doppler Effect, observing higher frequencies of a sound as it approaches, and lower frequencies as it moves farther away? How will our observed values compare to values calculated using known equations?. see here for answers. Vijayan Thanasekaran, Ashley Rodde and Gabriela Quiroz
Modeling the Doppler Effect using Audacity
Modeling the Doppler Effect using Audacity
Vijayan thanasekaran
Recommandé
Cours 1 du module "Piloter un projet informatique en bibliothèque". Formation initiale des élèves conservateurs territoriaux de bibliothèques - INET
L'écosystème informatique en bibliothèque : le SIGB
L'écosystème informatique en bibliothèque : le SIGB
Virginie Delaine
강현우, 권서현, 김지오, 박민지, 황다연
21-2 에어비앤비 리뷰평점 EDA 1팀
21-2 에어비앤비 리뷰평점 EDA 1팀
DataScienceLab
This developer-focused webinar will explain how to use the Cypher graph query language. Cypher, a query language designed specifically for graphs, allows for expressing complex graph patterns using simple ASCII art-like notation and offers a simple but expressive approach for working with graph data. During this webinar you'll learn: -Basic Cypher syntax -How to construct graph patterns using Cypher -Querying existing data -Data import with Cypher -Using aggregations such as statistical functions -Extending the power of Cypher using procedures and functions
Intro to Cypher
Intro to Cypher
Neo4j
6기 EDA 프로젝트 5조(김도언, 박세승, 박수빈, 박준우, 이승재)
Airbnb 리뷰데이터 분석을 통한 좋은 숙소의 조건 분석
Airbnb 리뷰데이터 분석을 통한 좋은 숙소의 조건 분석
DataScienceLab
The journey - ANN to Generative AI
Generative AI and Security (1).pptx.pdf
Generative AI and Security (1).pptx.pdf
Priyanka Aash
For companies that solve real-world problems and generate revenue from the data science products, being able to understand why a model makes a certain prediction can be as crucial as achieving high prediction accuracy in many applications. However, as data scientists pursuing higher accuracy by implementing complex algorithms such as ensemble or deep learning models, the algorithm itself becomes a blackbox and it creates the trade-off between accuracy and interpretability of a model’s output. To address this problem, a unified framework SHAP (SHapley Additive exPlanations) was developed to help users interpret the predictions of complex models. In this session, we will talk about how to apply SHAP to various modeling approaches (GLM, XGBoost, CNN) to explain how each feature contributes and extract intuitive insights from a particular prediction. This talk is intended to introduce the concept of general purpose model explainer, as well as help practitioners understand SHAP and its applications.
Unified Approach to Interpret Machine Learning Model: SHAP + LIME
Unified Approach to Interpret Machine Learning Model: SHAP + LIME
Databricks
6기 EDA 프로젝트 1조(강현우, 권서현, 김지오, 박민지, 황다연)
에어비앤비 리뷰데이터 분석을 통한 지역별 호스트 전략 제언
에어비앤비 리뷰데이터 분석을 통한 지역별 호스트 전략 제언
DataScienceLab
Modeling the Doppler Effect using Audacity. Can we model the Doppler Effect, observing higher frequencies of a sound as it approaches, and lower frequencies as it moves farther away? How will our observed values compare to values calculated using known equations?. see here for answers. Vijayan Thanasekaran, Ashley Rodde and Gabriela Quiroz
Modeling the Doppler Effect using Audacity
Modeling the Doppler Effect using Audacity
Vijayan thanasekaran
김기도(olaf.kido) / kakao corp.(미래미디어파트) --- 사용자에게 알맞은 뉴스를 전달하기 위해서는 언론사에서 전달해주는 기본 정보 이외에도 컨텐츠의 다양한 특성을 파악하여 이를 사용자와 연결 짓는 것이 중요합니다. 다양한 특성 정보들 중에서 기사의 유형이나 핵심 주제 같은 것들은 컨텐츠 본문을 자연어 처리해서만 얻을 수 있기 때문에 분석하기가 매우 까다롭습니다. 본 발표에서는 Deep Learning 기술을 사용한 '뉴스 메타 태깅 시스템'의 개발 사례를 소개합니다. 이 사례를 통해 분석 모델 학습부터 운영 시스템 개발 과정에서의 고민과 Lessons Learned를 공유하도록 하겠습니다.
딥러닝을 활용한 뉴스 메타 태깅
딥러닝을 활용한 뉴스 메타 태깅
if kakao
Cours de Lionel Maltese enseignant, chercheur et entrepreneur.
Marketing Evénementiel Sportif - Electif Master ESC - séance 2
Marketing Evénementiel Sportif - Electif Master ESC - séance 2
Guillaume LAURIE
Pourquoi veiller? Comment veiller?
Qu'est ce que la veille informationnelle ?
Qu'est ce que la veille informationnelle ?
LPLECORBUSIER
Comment rechercher, évaluer et présenter l'information en économie et gestion.
Recherche documentaire économie gestion
Recherche documentaire économie gestion
Université Aix-Marseille - Service commun de la documentation
History of the IntelliJ IDEA codebase and development practices used in its development.
From Renamer Plugin to Polyglot IDE
From Renamer Plugin to Polyglot IDE
intelliyole
Managing digital assets and instance-level metadata is critical to many company's business. It affects everything from content availability to analysis of customer usage behavior to the ability to get insights to monetization potential, and drive business innovation. In this session Jesús will explain how companies are leveraging the advantages of a graph platform like Neo4j over traditional relational databases and other types of data and metadata stores for DAM and discuss the success stories of Scripps Networks and Adobe Behance.
Graph-Powered Digital Asset Management with Neo4j
Graph-Powered Digital Asset Management with Neo4j
Neo4j
Ontology quality, ontology design patterns, and competency questions
Ontology quality, ontology design patterns, and competency questions
Nicola Guarino
Cette grille va vous permettre d'évaluation vos élèves sur la webquest "Le Tour de France en 10 étapes".
Grille pour l'enseignant
Grille pour l'enseignant
dorianel3fle
Intro to Neo4j Lju Lazarevic, Neo4j
Training Week: Introduction to Neo4j
Training Week: Introduction to Neo4j
Neo4j
The companion slides from the April 2023 "Where did you get that book" survey webinar from the Freckle Project. For more information and to see other surveys, please visit https://www.everylibraryinstitute.org/freckle_project_surveys_reports.
Freckle Project - April 2023 Survey Results - 6th Survey.pdf
Freckle Project - April 2023 Survey Results - 6th Survey.pdf
EveryLibrary
How are personal knowledge graphs evolving? What functionality should they include? What are some of the examples of emerging PKG platforms?
Paths to more personal and collaborative knowledge graphs
Paths to more personal and collaborative knowledge graphs
Alan Morrison
Our ride with Snowflake began 4 years ago. We faced the daunting task of building a decentralized data platform that could empower our 50+ engineering and analytical teams with autonomy while complying with international regulations. Snowflake has quickly become an essential component of our platform, enabling new cross-teams and cross-department data-sharing scenarios that have led to significant time-to-market and cost reductions (up to 2x). Fine-grained RBAC allows us to quickly adapt to rapidly changing local and international compliance regulations. Nowadays, we are proud to present our distributed data platform based on Snowflake, which adheres to fundamental data-mesh principles.
FlixBus Ride with Snowflake
FlixBus Ride with Snowflake
Taras Slipets
La recherche d\'information sur internet
La recherche d\'information sur internet
La recherche d\'information sur internet
alexartiste
Tutorial "Getting Started With Knowledge Graphs" Given at ESWC 2017
ESWC 2017 Tutorial Knowledge Graphs
ESWC 2017 Tutorial Knowledge Graphs
Peter Haase
These are the slides from the Graph Analytics with ArangoDB webinar from February 2021: https://www.arangodb.com/events/graph-analytics-with-arangodb/
Graph Analytics with ArangoDB
Graph Analytics with ArangoDB
ArangoDB Database
Introduction to DBpedia, the most popular and interconnected source of Linked Open Data. Part of EXPLORING WIKIDATA AND THE SEMANTIC WEB FOR LIBRARIES at METRO http://metro.org/events/598/
DBpedia InsideOut
DBpedia InsideOut
Cristina Pattuelli
Marco Bessi, Neo4j Riccardo Ciarlo, Neo4j
Neo4j Graph Data Science - Webinar
Neo4j Graph Data Science - Webinar
Neo4j
This workshop presentation from Enterprise Knowledge team members Joe Hilger, Founder and COO, and Sara Nash, Technical Analyst, was delivered on June 8, 2020 as part of the Data Summit 2020 virtual conference. The 3-hour workshop provided an interdisciplinary group of participants with a definition of what a knowledge graph is, how it is implemented, and how it can be used to increase the value of your organization’s datas. This slide deck gives an overview of the KM concepts that are necessary for the implementation of knowledge graphs as a foundation for Enterprise Artificial Intelligence (AI). Hilger and Nash also outlined four use cases for knowledge graphs, including recommendation engines and natural language query on structured data.
Introduction to Knowledge Graphs: Data Summit 2020
Introduction to Knowledge Graphs: Data Summit 2020
Enterprise Knowledge
Unicef2
Unicef2
Ralf buda
Unicef
Unicef
Ralf buda
UNICEF
UNICEF
Jorge Heorhiyan
VWC Vortrag von Thomas Praus
Gesellschaftliche Gründe Für die Flucht In Virtuelle Welten
Gesellschaftliche Gründe Für die Flucht In Virtuelle Welten
guest62f159
Contenu connexe
Tendances
김기도(olaf.kido) / kakao corp.(미래미디어파트) --- 사용자에게 알맞은 뉴스를 전달하기 위해서는 언론사에서 전달해주는 기본 정보 이외에도 컨텐츠의 다양한 특성을 파악하여 이를 사용자와 연결 짓는 것이 중요합니다. 다양한 특성 정보들 중에서 기사의 유형이나 핵심 주제 같은 것들은 컨텐츠 본문을 자연어 처리해서만 얻을 수 있기 때문에 분석하기가 매우 까다롭습니다. 본 발표에서는 Deep Learning 기술을 사용한 '뉴스 메타 태깅 시스템'의 개발 사례를 소개합니다. 이 사례를 통해 분석 모델 학습부터 운영 시스템 개발 과정에서의 고민과 Lessons Learned를 공유하도록 하겠습니다.
딥러닝을 활용한 뉴스 메타 태깅
딥러닝을 활용한 뉴스 메타 태깅
if kakao
Cours de Lionel Maltese enseignant, chercheur et entrepreneur.
Marketing Evénementiel Sportif - Electif Master ESC - séance 2
Marketing Evénementiel Sportif - Electif Master ESC - séance 2
Guillaume LAURIE
Pourquoi veiller? Comment veiller?
Qu'est ce que la veille informationnelle ?
Qu'est ce que la veille informationnelle ?
LPLECORBUSIER
Comment rechercher, évaluer et présenter l'information en économie et gestion.
Recherche documentaire économie gestion
Recherche documentaire économie gestion
Université Aix-Marseille - Service commun de la documentation
History of the IntelliJ IDEA codebase and development practices used in its development.
From Renamer Plugin to Polyglot IDE
From Renamer Plugin to Polyglot IDE
intelliyole
Managing digital assets and instance-level metadata is critical to many company's business. It affects everything from content availability to analysis of customer usage behavior to the ability to get insights to monetization potential, and drive business innovation. In this session Jesús will explain how companies are leveraging the advantages of a graph platform like Neo4j over traditional relational databases and other types of data and metadata stores for DAM and discuss the success stories of Scripps Networks and Adobe Behance.
Graph-Powered Digital Asset Management with Neo4j
Graph-Powered Digital Asset Management with Neo4j
Neo4j
Ontology quality, ontology design patterns, and competency questions
Ontology quality, ontology design patterns, and competency questions
Nicola Guarino
Cette grille va vous permettre d'évaluation vos élèves sur la webquest "Le Tour de France en 10 étapes".
Grille pour l'enseignant
Grille pour l'enseignant
dorianel3fle
Intro to Neo4j Lju Lazarevic, Neo4j
Training Week: Introduction to Neo4j
Training Week: Introduction to Neo4j
Neo4j
The companion slides from the April 2023 "Where did you get that book" survey webinar from the Freckle Project. For more information and to see other surveys, please visit https://www.everylibraryinstitute.org/freckle_project_surveys_reports.
Freckle Project - April 2023 Survey Results - 6th Survey.pdf
Freckle Project - April 2023 Survey Results - 6th Survey.pdf
EveryLibrary
How are personal knowledge graphs evolving? What functionality should they include? What are some of the examples of emerging PKG platforms?
Paths to more personal and collaborative knowledge graphs
Paths to more personal and collaborative knowledge graphs
Alan Morrison
Our ride with Snowflake began 4 years ago. We faced the daunting task of building a decentralized data platform that could empower our 50+ engineering and analytical teams with autonomy while complying with international regulations. Snowflake has quickly become an essential component of our platform, enabling new cross-teams and cross-department data-sharing scenarios that have led to significant time-to-market and cost reductions (up to 2x). Fine-grained RBAC allows us to quickly adapt to rapidly changing local and international compliance regulations. Nowadays, we are proud to present our distributed data platform based on Snowflake, which adheres to fundamental data-mesh principles.
FlixBus Ride with Snowflake
FlixBus Ride with Snowflake
Taras Slipets
La recherche d\'information sur internet
La recherche d\'information sur internet
La recherche d\'information sur internet
alexartiste
Tutorial "Getting Started With Knowledge Graphs" Given at ESWC 2017
ESWC 2017 Tutorial Knowledge Graphs
ESWC 2017 Tutorial Knowledge Graphs
Peter Haase
These are the slides from the Graph Analytics with ArangoDB webinar from February 2021: https://www.arangodb.com/events/graph-analytics-with-arangodb/
Graph Analytics with ArangoDB
Graph Analytics with ArangoDB
ArangoDB Database
Introduction to DBpedia, the most popular and interconnected source of Linked Open Data. Part of EXPLORING WIKIDATA AND THE SEMANTIC WEB FOR LIBRARIES at METRO http://metro.org/events/598/
DBpedia InsideOut
DBpedia InsideOut
Cristina Pattuelli
Marco Bessi, Neo4j Riccardo Ciarlo, Neo4j
Neo4j Graph Data Science - Webinar
Neo4j Graph Data Science - Webinar
Neo4j
This workshop presentation from Enterprise Knowledge team members Joe Hilger, Founder and COO, and Sara Nash, Technical Analyst, was delivered on June 8, 2020 as part of the Data Summit 2020 virtual conference. The 3-hour workshop provided an interdisciplinary group of participants with a definition of what a knowledge graph is, how it is implemented, and how it can be used to increase the value of your organization’s datas. This slide deck gives an overview of the KM concepts that are necessary for the implementation of knowledge graphs as a foundation for Enterprise Artificial Intelligence (AI). Hilger and Nash also outlined four use cases for knowledge graphs, including recommendation engines and natural language query on structured data.
Introduction to Knowledge Graphs: Data Summit 2020
Introduction to Knowledge Graphs: Data Summit 2020
Enterprise Knowledge
Tendances
(18)
딥러닝을 활용한 뉴스 메타 태깅
딥러닝을 활용한 뉴스 메타 태깅
Marketing Evénementiel Sportif - Electif Master ESC - séance 2
Marketing Evénementiel Sportif - Electif Master ESC - séance 2
Qu'est ce que la veille informationnelle ?
Qu'est ce que la veille informationnelle ?
Recherche documentaire économie gestion
Recherche documentaire économie gestion
From Renamer Plugin to Polyglot IDE
From Renamer Plugin to Polyglot IDE
Graph-Powered Digital Asset Management with Neo4j
Graph-Powered Digital Asset Management with Neo4j
Ontology quality, ontology design patterns, and competency questions
Ontology quality, ontology design patterns, and competency questions
Grille pour l'enseignant
Grille pour l'enseignant
Training Week: Introduction to Neo4j
Training Week: Introduction to Neo4j
Freckle Project - April 2023 Survey Results - 6th Survey.pdf
Freckle Project - April 2023 Survey Results - 6th Survey.pdf
Paths to more personal and collaborative knowledge graphs
Paths to more personal and collaborative knowledge graphs
FlixBus Ride with Snowflake
FlixBus Ride with Snowflake
La recherche d\'information sur internet
La recherche d\'information sur internet
ESWC 2017 Tutorial Knowledge Graphs
ESWC 2017 Tutorial Knowledge Graphs
Graph Analytics with ArangoDB
Graph Analytics with ArangoDB
DBpedia InsideOut
DBpedia InsideOut
Neo4j Graph Data Science - Webinar
Neo4j Graph Data Science - Webinar
Introduction to Knowledge Graphs: Data Summit 2020
Introduction to Knowledge Graphs: Data Summit 2020
En vedette
Unicef2
Unicef2
Ralf buda
Unicef
Unicef
Ralf buda
UNICEF
UNICEF
Jorge Heorhiyan
VWC Vortrag von Thomas Praus
Gesellschaftliche Gründe Für die Flucht In Virtuelle Welten
Gesellschaftliche Gründe Für die Flucht In Virtuelle Welten
guest62f159
Farben
Farben
Ralf buda
2010-04-12 FNF BaaA - n°13-pakistan_von präsidial- zu parlamentsdemokratie
2010-04-12 FNF BaaA - n°13-pakistan_von präsidial- zu parlamentsdemokratie
Olaf Kellerhoff
96101502
96101502
Guido Leenders
Solamente la lombriz californiana es capaz de alimentarse con la misma cantidad de peso que tiene,pesa 1 gramos y consume 1 gramo de desechos orgánicos,el 80% para la producción y 20 % para su metabolismo.
Lombricultura 2
Lombricultura 2
Colegios Técnicos Agropecuarios de Cordillera
Parte practica
Parte practica
Parte practica
leli1234
Windows
Windows
Windows
Matilde Blanco Peña
Objetos
Objetos
Objetos
Meell Rojas Altamirano
Workshop Adobe Formulare für SAP Business ByDesign
Workshop Adobe Formulare für SAP Business ByDesign
anthesis GmbH
Documentación e implementacion de un SGC
Documentación e implementacion de un SGC
Documentación e implementacion de un SGC
SGCGRUPOUNEFM
Presentación cicleteros
Presentacion cicleteros
Presentacion cicleteros
cantallopts2
2 presentacion economia camila
2 presentacion economia camila
Kamy Guevara
Líderes
Líderes
zdfhdcgfnj
Análisis sobre sistemas de información y su relación
Análisis sobre sistemas de información y su relación
rorvan
Practica nro 6 laboratorio de circuitos
Pre 6
Pre 6
Guillermo Chirinos
Mit Logstash erhält man eine sehr gute Open Source Lösung, wenn es um das archivieren und sammeln von Logfiles geht. Nicht nur Syslog oder klassische Logfiles können abgegriffen werden, sondern auch das Windows Event-Log oder SNMP-Traps. Diese können anschließend in einem intuitiven Webinterface gefiltert und ausgewertet werden. Webinare Archiv Link: https://www.netways.de/webinare/archiv/logstash_webinare/logstash_open_source_log_management/ Aktuell: https://www.netways.de/webinare/webinare_aktuell/ NETWAYS Konferenzen: https://www.netways.de/events_schulungen/home/ Schulungen: https://www.netways.de/events_schulungen/schulungen/home/ Shop: https://shop.netways.de/ Blog: http://blog.netways.de/ Social Media YouTube: https://www.youtube.com/channel/UC8nIBEFmjzXjXeJV_hkkeIQ Facebook: https://www.facebook.com/netways Google+: https://plus.google.com/+netways/ Twitter: https://twitter.com/netways
Logstash: Open Source Log-Management (Webinar vom 20.02.2014)
Logstash: Open Source Log-Management (Webinar vom 20.02.2014)
NETWAYS
Grundladgen des Berichtwesen und Arbeiten mit Berichten
Grundladgen des Berichtwesen und Arbeiten mit Berichten
anthesis GmbH
En vedette
(20)
Unicef2
Unicef2
Unicef
Unicef
UNICEF
UNICEF
Gesellschaftliche Gründe Für die Flucht In Virtuelle Welten
Gesellschaftliche Gründe Für die Flucht In Virtuelle Welten
Farben
Farben
2010-04-12 FNF BaaA - n°13-pakistan_von präsidial- zu parlamentsdemokratie
2010-04-12 FNF BaaA - n°13-pakistan_von präsidial- zu parlamentsdemokratie
96101502
96101502
Lombricultura 2
Lombricultura 2
Parte practica
Parte practica
Windows
Windows
Objetos
Objetos
Workshop Adobe Formulare für SAP Business ByDesign
Workshop Adobe Formulare für SAP Business ByDesign
Documentación e implementacion de un SGC
Documentación e implementacion de un SGC
Presentacion cicleteros
Presentacion cicleteros
2 presentacion economia camila
2 presentacion economia camila
Líderes
Líderes
Análisis sobre sistemas de información y su relación
Análisis sobre sistemas de información y su relación
Pre 6
Pre 6
Logstash: Open Source Log-Management (Webinar vom 20.02.2014)
Logstash: Open Source Log-Management (Webinar vom 20.02.2014)
Grundladgen des Berichtwesen und Arbeiten mit Berichten
Grundladgen des Berichtwesen und Arbeiten mit Berichten
Plus de Ralf buda
1. Was ist ein Wiki und was ist das DSD-Wiki? 2. Die Wiki-Family auf ZUM.de 3. Warum ich ein Wiki nutze? 4. Möglichkeiten eines Wikis 5. Beispiele der Arbeit im Wiki 5.1 Projektarbeit 5.2 Konkrete Schülerarbeiten im Wiki 6. Wiki-Baukasten 7. Ausblick
Wiki im Fremdsprachenunterricht
Wiki im Fremdsprachenunterricht
Ralf buda
Weiterbildung
Weiterbildung
Ralf buda
Der Malteser Hilfsdienst Vr2
Der Malteser Hilfsdienst Vr2
Ralf buda
Ungarische Ökumenische Hiflsorganisation
Ungarische Ökumenische Hiflsorganisation
Ralf buda
Die Ungarische Ökumenische Hilfsorganisation
Die Ungarische Ökumenische Hilfsorganisation
Ralf buda
WWF-2
WWF-2
Ralf buda
United Nations High Commissiner For Refugees2
United Nations High Commissiner For Refugees2
Ralf buda
UNHCR
UNHCR
Ralf buda
Das Kindermissionswerk
Das Kindermissionswerk
Ralf buda
Ärzte Ohne Grenzen
Ärzte Ohne Grenzen
Ralf buda
Amnesty International
Amnesty International
Ralf buda
Amnesty International 2
Amnesty International 2
Ralf buda
WWF
WWF
Ralf buda
Das Übergewicht als Gesellschaftliches Problem
Das Übergewicht als Gesellschaftliches Problem
Ralf buda
Fahrrad
Fahrrad
Ralf buda
Sterbehilfe
Sterbehilfe
Ralf buda
Doping Im Spitzensport
Doping Im Spitzensport
Ralf buda
Weihnachten Bei Uns
Weihnachten Bei Uns
Ralf buda
Was sind typische Weihnachtsbräuche in Ungarn?
Weihnachten In Ungarn
Weihnachten In Ungarn
Ralf buda
Zum Wiki Format2
Zum Wiki Format2
Ralf buda
Plus de Ralf buda
(20)
Wiki im Fremdsprachenunterricht
Wiki im Fremdsprachenunterricht
Weiterbildung
Weiterbildung
Der Malteser Hilfsdienst Vr2
Der Malteser Hilfsdienst Vr2
Ungarische Ökumenische Hiflsorganisation
Ungarische Ökumenische Hiflsorganisation
Die Ungarische Ökumenische Hilfsorganisation
Die Ungarische Ökumenische Hilfsorganisation
WWF-2
WWF-2
United Nations High Commissiner For Refugees2
United Nations High Commissiner For Refugees2
UNHCR
UNHCR
Das Kindermissionswerk
Das Kindermissionswerk
Ärzte Ohne Grenzen
Ärzte Ohne Grenzen
Amnesty International
Amnesty International
Amnesty International 2
Amnesty International 2
WWF
WWF
Das Übergewicht als Gesellschaftliches Problem
Das Übergewicht als Gesellschaftliches Problem
Fahrrad
Fahrrad
Sterbehilfe
Sterbehilfe
Doping Im Spitzensport
Doping Im Spitzensport
Weihnachten Bei Uns
Weihnachten Bei Uns
Weihnachten In Ungarn
Weihnachten In Ungarn
Zum Wiki Format2
Zum Wiki Format2
Unicef
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Gibt es Fragen
9.
Vielen Dank für
I hre Aufmerksamkeit! Tamás Barabás 10/A
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