Submit Search
Upload
Data Formats
•
Download as PPT, PDF
•
0 likes
•
974 views
S
setitesuk
Follow
A brief talk describing soem different plain text data format styles
Read less
Read more
Technology
Report
Share
Report
Share
1 of 19
Download now
Recommended
big data
Big data-analytics-cpe8035
Big data-analytics-cpe8035
Neelam Rawat
slides contain: Bayesian Belief Networks, Classification by Backpropagation, Support Vector Machines, Classification by Using Frequent Patterns, Lazy Learners, (or Learning from Your Neighbors) Other Classification Methods, Additional Topics Regarding Classification, Summary by Jiawei Han, Micheline Kamber, and Jian Pei, University of Illinois at Urbana-Champaign & Simon Fraser University, ©2013 Han, Kamber & Pei. All rights reserved.
Data Mining: Concepts and techniques classification _chapter 9 :advanced methods
Data Mining: Concepts and techniques classification _chapter 9 :advanced methods
Salah Amean
Database
Database
Database
Bhandari Nawaraj
Data Processing in the Cloud with Hadoop from Data Services World conference.
Cloud Computing: Hadoop
Cloud Computing: Hadoop
darugar
File Organization
File Organization
Manyi Man
3 Tier Architecture
3 Tier Architecture
Webx
Caffe - A deep learning framework (Ramin Fahimi)
Caffe - A deep learning framework (Ramin Fahimi)
Caffe - A deep learning framework (Ramin Fahimi)
irpycon
Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Setting up the Hadoop Cluster, Map-Reduce,PIG, HIVE, HBase, Zookeeper, SQOOP etc. will be covered in the course.
Big Data & Hadoop Tutorial
Big Data & Hadoop Tutorial
Edureka!
Recommended
big data
Big data-analytics-cpe8035
Big data-analytics-cpe8035
Neelam Rawat
slides contain: Bayesian Belief Networks, Classification by Backpropagation, Support Vector Machines, Classification by Using Frequent Patterns, Lazy Learners, (or Learning from Your Neighbors) Other Classification Methods, Additional Topics Regarding Classification, Summary by Jiawei Han, Micheline Kamber, and Jian Pei, University of Illinois at Urbana-Champaign & Simon Fraser University, ©2013 Han, Kamber & Pei. All rights reserved.
Data Mining: Concepts and techniques classification _chapter 9 :advanced methods
Data Mining: Concepts and techniques classification _chapter 9 :advanced methods
Salah Amean
Database
Database
Database
Bhandari Nawaraj
Data Processing in the Cloud with Hadoop from Data Services World conference.
Cloud Computing: Hadoop
Cloud Computing: Hadoop
darugar
File Organization
File Organization
Manyi Man
3 Tier Architecture
3 Tier Architecture
Webx
Caffe - A deep learning framework (Ramin Fahimi)
Caffe - A deep learning framework (Ramin Fahimi)
Caffe - A deep learning framework (Ramin Fahimi)
irpycon
Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Setting up the Hadoop Cluster, Map-Reduce,PIG, HIVE, HBase, Zookeeper, SQOOP etc. will be covered in the course.
Big Data & Hadoop Tutorial
Big Data & Hadoop Tutorial
Edureka!
Decision Tree - C4.5&CART
Decision Tree - C4.5&CART
Xueping Peng
Files organization
File Organization
File Organization
RAMPRAKASH REDDY ARAVA
This PPT gives Information about: 1. PHP Basic syntax, 2. PHP data Types, 3. PHP Variables, 4. PHP Constants, 5. PHP Expressions, 6. PHP Operators, 7. PHP Control Structures, 8. PHP Loops
PHP - Introduction to PHP Fundamentals
PHP - Introduction to PHP Fundamentals
Vibrant Technologies & Computers
Brief description of Hive
Hive(ppt)
Hive(ppt)
Abhinav Tyagi
The most well known technology used for Big Data is Hadoop. It is actually a large scale batch data processing system
HADOOP TECHNOLOGY ppt
HADOOP TECHNOLOGY ppt
sravya raju
presentation on Apache hadoop
PPT on Hadoop
PPT on Hadoop
Shubham Parmar
Multivariate Data Visualization
Multivariate Data Visualization
anilash
information system
Database management system
Database management system
RizwanHafeez
Hadoop Overview & Architecture
Hadoop Overview & Architecture
Hadoop Overview & Architecture
EMC
This Edureka Tableau Dashboard Tutorial (Tableau Dashboard Blog: https://goo.gl/Wx2ef9) helps you understand how to make visualizations and create a Tableau Dashboard. The entire demo gets carried out with a IPL Dataset to help you understand the concepts in a fun and easy way.
Tableau Dashboard Tutorial | Tableau Training For Beginners | Tableau Tutoria...
Tableau Dashboard Tutorial | Tableau Training For Beginners | Tableau Tutoria...
Edureka!
Introduction to Big Data
Chapter 1 big data
Chapter 1 big data
Prof .Pragati Khade
This presentation briefly discusses about the following topics: Data Analytics Lifecycle Importance of Data Analytics Lifecycle Phase 1: Discovery Phase 2: Data Preparation Phase 3: Model Planning Phase 4: Model Building Phase 5: Communication Results Phase 6: Operationalize Data Analytics Lifecycle Example
Data Analytics Life Cycle
Data Analytics Life Cycle
Dr. C.V. Suresh Babu
Apache Pig: Introduction, Description, Installation, Pig Latin Commands, Use, Examples, Usefulness are demonstrated in this presentation. Tushar B. Kute Researcher, http://tusharkute.com
Apache Pig: A big data processor
Apache Pig: A big data processor
Tushar B Kute
RDataMining Slides Series: Data Exploration and Visualization with R
Data Exploration and Visualization with R
Data Exploration and Visualization with R
Yanchang Zhao
An in-depth (110 slides) tutorial on DDS and the RTI Data-Distribution Service Updated for 2011
RTI Data-Distribution Service (DDS) Master Class 2011
RTI Data-Distribution Service (DDS) Master Class 2011
Gerardo Pardo-Castellote
business intelligence Data warehouse design steps and methods
Data warehouse design
Data warehouse design
ines beltaief
Data Model: A set of concepts to describe the structure of a database, the operations for manipulating these structures, and certain constraints that the database should obey.
Adbms 5 data models schemas instances and states
Adbms 5 data models schemas instances and states
Vaibhav Khanna
Hadoop Map Reduce
Hadoop Map Reduce
VNIT-ACM Student Chapter
Data Warehouse Modeling
Data Warehouse Modeling
vivekjv
Sever 2016
1 introduction to windows server 2016
1 introduction to windows server 2016
Hameda Hurmat
A slideshow showing the development of a pluggable pipeline system
Pluggable Pipelines
Pluggable Pipelines
setitesuk
Talk given at Software East's Nov 2010 meeting, location - RedGate Software, Cambridge, UK
Agile analysis development
Agile analysis development
setitesuk
More Related Content
What's hot
Decision Tree - C4.5&CART
Decision Tree - C4.5&CART
Xueping Peng
Files organization
File Organization
File Organization
RAMPRAKASH REDDY ARAVA
This PPT gives Information about: 1. PHP Basic syntax, 2. PHP data Types, 3. PHP Variables, 4. PHP Constants, 5. PHP Expressions, 6. PHP Operators, 7. PHP Control Structures, 8. PHP Loops
PHP - Introduction to PHP Fundamentals
PHP - Introduction to PHP Fundamentals
Vibrant Technologies & Computers
Brief description of Hive
Hive(ppt)
Hive(ppt)
Abhinav Tyagi
The most well known technology used for Big Data is Hadoop. It is actually a large scale batch data processing system
HADOOP TECHNOLOGY ppt
HADOOP TECHNOLOGY ppt
sravya raju
presentation on Apache hadoop
PPT on Hadoop
PPT on Hadoop
Shubham Parmar
Multivariate Data Visualization
Multivariate Data Visualization
anilash
information system
Database management system
Database management system
RizwanHafeez
Hadoop Overview & Architecture
Hadoop Overview & Architecture
Hadoop Overview & Architecture
EMC
This Edureka Tableau Dashboard Tutorial (Tableau Dashboard Blog: https://goo.gl/Wx2ef9) helps you understand how to make visualizations and create a Tableau Dashboard. The entire demo gets carried out with a IPL Dataset to help you understand the concepts in a fun and easy way.
Tableau Dashboard Tutorial | Tableau Training For Beginners | Tableau Tutoria...
Tableau Dashboard Tutorial | Tableau Training For Beginners | Tableau Tutoria...
Edureka!
Introduction to Big Data
Chapter 1 big data
Chapter 1 big data
Prof .Pragati Khade
This presentation briefly discusses about the following topics: Data Analytics Lifecycle Importance of Data Analytics Lifecycle Phase 1: Discovery Phase 2: Data Preparation Phase 3: Model Planning Phase 4: Model Building Phase 5: Communication Results Phase 6: Operationalize Data Analytics Lifecycle Example
Data Analytics Life Cycle
Data Analytics Life Cycle
Dr. C.V. Suresh Babu
Apache Pig: Introduction, Description, Installation, Pig Latin Commands, Use, Examples, Usefulness are demonstrated in this presentation. Tushar B. Kute Researcher, http://tusharkute.com
Apache Pig: A big data processor
Apache Pig: A big data processor
Tushar B Kute
RDataMining Slides Series: Data Exploration and Visualization with R
Data Exploration and Visualization with R
Data Exploration and Visualization with R
Yanchang Zhao
An in-depth (110 slides) tutorial on DDS and the RTI Data-Distribution Service Updated for 2011
RTI Data-Distribution Service (DDS) Master Class 2011
RTI Data-Distribution Service (DDS) Master Class 2011
Gerardo Pardo-Castellote
business intelligence Data warehouse design steps and methods
Data warehouse design
Data warehouse design
ines beltaief
Data Model: A set of concepts to describe the structure of a database, the operations for manipulating these structures, and certain constraints that the database should obey.
Adbms 5 data models schemas instances and states
Adbms 5 data models schemas instances and states
Vaibhav Khanna
Hadoop Map Reduce
Hadoop Map Reduce
VNIT-ACM Student Chapter
Data Warehouse Modeling
Data Warehouse Modeling
vivekjv
Sever 2016
1 introduction to windows server 2016
1 introduction to windows server 2016
Hameda Hurmat
What's hot
(20)
Decision Tree - C4.5&CART
Decision Tree - C4.5&CART
File Organization
File Organization
PHP - Introduction to PHP Fundamentals
PHP - Introduction to PHP Fundamentals
Hive(ppt)
Hive(ppt)
HADOOP TECHNOLOGY ppt
HADOOP TECHNOLOGY ppt
PPT on Hadoop
PPT on Hadoop
Multivariate Data Visualization
Multivariate Data Visualization
Database management system
Database management system
Hadoop Overview & Architecture
Hadoop Overview & Architecture
Tableau Dashboard Tutorial | Tableau Training For Beginners | Tableau Tutoria...
Tableau Dashboard Tutorial | Tableau Training For Beginners | Tableau Tutoria...
Chapter 1 big data
Chapter 1 big data
Data Analytics Life Cycle
Data Analytics Life Cycle
Apache Pig: A big data processor
Apache Pig: A big data processor
Data Exploration and Visualization with R
Data Exploration and Visualization with R
RTI Data-Distribution Service (DDS) Master Class 2011
RTI Data-Distribution Service (DDS) Master Class 2011
Data warehouse design
Data warehouse design
Adbms 5 data models schemas instances and states
Adbms 5 data models schemas instances and states
Hadoop Map Reduce
Hadoop Map Reduce
Data Warehouse Modeling
Data Warehouse Modeling
1 introduction to windows server 2016
1 introduction to windows server 2016
Viewers also liked
A slideshow showing the development of a pluggable pipeline system
Pluggable Pipelines
Pluggable Pipelines
setitesuk
Talk given at Software East's Nov 2010 meeting, location - RedGate Software, Cambridge, UK
Agile analysis development
Agile analysis development
setitesuk
Slides for a presentation on testing given to foomongers at the EBI/Sanger Insts 2008/03/12
Test Presentation
Test Presentation
setitesuk
Prezentacja SLC Targi eHandlu Poznań 02.03.2012
20120301 prezentacja slc niezbędnik właściciela sklepu internetowego
20120301 prezentacja slc niezbędnik właściciela sklepu internetowego
marcinblaszyk
pipeline_structure_overview
pipeline_structure_overview
setitesuk
Lightning talk given at AgileCambridge2010 Good feedback, and generated plenty of discussion at the pub afterwards
Pomodoro lightning talk
Pomodoro lightning talk
setitesuk
Artificial intelligence (AI) is everywhere, promising self-driving cars, medical breakthroughs, and new ways of working. But how do you separate hype from reality? How can your company apply AI to solve real business problems? Here’s what AI learnings your business should keep in mind for 2017.
Hype vs. Reality: The AI Explainer
Hype vs. Reality: The AI Explainer
Luminary Labs
We asked LinkedIn members worldwide about their levels of interest in the latest wave of technology: whether they’re using wearables, and whether they intend to buy self-driving cars and VR headsets as they become available. We asked them too about their attitudes to technology and to the growing role of Artificial Intelligence (AI) in the devices that they use. The answers were fascinating – and in many cases, surprising. This SlideShare explores the full results of this study, including detailed market-by-market breakdowns of intention levels for each technology – and how attitudes change with age, location and seniority level. If you’re marketing a tech brand – or planning to use VR and wearables to reach a professional audience – then these are insights you won’t want to miss.
Study: The Future of VR, AR and Self-Driving Cars
Study: The Future of VR, AR and Self-Driving Cars
LinkedIn
Viewers also liked
(8)
Pluggable Pipelines
Pluggable Pipelines
Agile analysis development
Agile analysis development
Test Presentation
Test Presentation
20120301 prezentacja slc niezbędnik właściciela sklepu internetowego
20120301 prezentacja slc niezbędnik właściciela sklepu internetowego
pipeline_structure_overview
pipeline_structure_overview
Pomodoro lightning talk
Pomodoro lightning talk
Hype vs. Reality: The AI Explainer
Hype vs. Reality: The AI Explainer
Study: The Future of VR, AR and Self-Driving Cars
Study: The Future of VR, AR and Self-Driving Cars
Similar to Data Formats
eXtensible Markup Language
eXtensible Markup Language
Aditya Raj
Xml and Xhtml
xml and xhtml.pptx
xml and xhtml.pptx
ssusere16bd9
ALTERNATIVES TO JSON: YAML/TOML/... AND WHY?
Presentation
Presentation
IrinaDovgyalo
xml
Xml iet 2015
Xml iet 2015
kiransurariya
XML Technologies
XML Technologies
juancpinzone
XML Technologies
XML Technologies
juancpinzone
The method of using XML documents for current storing and displaying and then updating later in the database can be used in web pages where frequently changing data has to be displayed like live score card, stock exchange report, weather details as wind direction, wind speed, temperature etc. and many more areas. In our project, we are making a web based application that will display the live scores of any live cricket game.
Web based application of Live Scoreboard using XML.
Web based application of Live Scoreboard using XML.
Uttam Kumar
By now, you have heard how important structured content is. But, maybe you poked around with something like DITA and were baffled by the complexity. Or, maybe you still aren’t sure what XSLT stands for. This workshop will take participants back to the basics, to provide a foundation for higher-level concepts that have taken hold of our industry. Topics will include: - What XML looks like, what it does, and how to create it. - How to define a structure model, including whether to use a - DTD, Schema, etc. - What XSLT looks like, what it does, and how to make it work. - What DITA and DocBook really are and whether one is right for you. Russell Ward is an experienced technical writer and structured technologies developer. He has spent many years working with structured content to maximize efficiency in the techcomm environment, both as an employee and as an independent consultant. He is also an experienced trainer and speaks periodically at conferences and other peer events.
Markup For Dummies (Russ Ward)
Markup For Dummies (Russ Ward)
STC-Philadelphia Metro Chapter
Introduction to xml
Introduction to xml
soumya
ASP Lesson...
Xml
Xml
Vanndy Sun
Complete XML
Xml
Xml
Venkat Krishnan
An introduction to Azure Data Lake for those already familiar with SQL Server. Presented at SQL Saturday Indianapolis on 17 August 2019
Dipping Your Toes: Azure Data Lake for DBAs
Dipping Your Toes: Azure Data Lake for DBAs
Bob Pusateri
Although animals do not use language, they are capable of many of the same kinds of cognition as us; much of our experience is at a non-verbal level. Semantics is the bridge between surface forms used in language and what we do and experience. Language understanding depends on world knowledge (i.e. “the pig is in the pen” vs. “the ink is in the pen”) We might not be ready for executives to specify policies themselves, but we can make the process from specification to behavior more automated, linked to precise vocabulary, and more traceable. Advances such as SVBR and an English serialization for ISO Common Logic means that executives and line workers can understand why the system does certain things, or verify that policies and regulations are implemented
Making the semantic web work
Making the semantic web work
Paul Houle
Big Data Compression techniques
Hadoop compression strata conference
Hadoop compression strata conference
nkabra
XML is a markup language which is used for storing and exchanging data. A markup language marks up the text syntactically in a document under different tags and hence makes the text distinguishable. XML stores data in the form of a structured document; these documents are used for creating web pages and for transporting data. Copy the link given below and paste it in new browser window to get more information on XML:- http://www.transtutors.com/homework-help/computer-science/xml.aspx
XML | Computer Science
XML | Computer Science
Transweb Global Inc
XML Intro
01 Xml Begin
01 Xml Begin
Dennis Pipper
Tis is a presentation from aeries of slides on the concepts of web, Library Automation for MLIS students
XML
XML
Vahideh Zarea Gavgani
Recently a new breed of "multi-model" databases has emerged. They are a document store, a graph database and a key/value store combined in one program. Therefore they are able to cover a lot of use cases which otherwise would need multiple different database systems. This approach promises a boost to the idea of "polyglot persistence", which has become very popular in recent years although it creates some friction in the form of data conversion and synchronisation between different systems. This is, because with a multi-model database one can enjoy the benefits of polyglot persistence without the disadvantages. In this talk I will explain the motivation behind the multi-model approach, discuss its advantages and limitations, and will then risk to make some predictions about the NoSQL database market in five years time, which I shall only reveal during the talk.
Is multi-model the future of NoSQL?
Is multi-model the future of NoSQL?
Max Neunhöffer
Human users should not be forced to edit XML documents. Sometimes, they may want to read it. The presentation persists some arguments I stated about this topic again and again in the past. Discussions and opinions are more than welcome.
Humans should not write XML.
Humans should not write XML.
Peter Tröger
XML Databases
XML Databases
Jussi Pohjolainen
Similar to Data Formats
(20)
eXtensible Markup Language
eXtensible Markup Language
xml and xhtml.pptx
xml and xhtml.pptx
Presentation
Presentation
Xml iet 2015
Xml iet 2015
XML Technologies
XML Technologies
XML Technologies
XML Technologies
Web based application of Live Scoreboard using XML.
Web based application of Live Scoreboard using XML.
Markup For Dummies (Russ Ward)
Markup For Dummies (Russ Ward)
Introduction to xml
Introduction to xml
Xml
Xml
Xml
Xml
Dipping Your Toes: Azure Data Lake for DBAs
Dipping Your Toes: Azure Data Lake for DBAs
Making the semantic web work
Making the semantic web work
Hadoop compression strata conference
Hadoop compression strata conference
XML | Computer Science
XML | Computer Science
01 Xml Begin
01 Xml Begin
XML
XML
Is multi-model the future of NoSQL?
Is multi-model the future of NoSQL?
Humans should not write XML.
Humans should not write XML.
XML Databases
XML Databases
Recently uploaded
The presentation from our live stream where we shared insights from our new research into the 2024 Smart Building Startup Landscape. Memoori has seen a 33% Decrease in Funding Rounds Compared to the Previous Year. However, with $3.5 Billion invested in 2023 and over $2 Billion already invested in the first 4 months of 2024, the outlook for investment remains positive.
State of the Smart Building Startup Landscape 2024!
State of the Smart Building Startup Landscape 2024!
Memoori
Generative AI refers to a class of machine learning algorithms that are designed to generate new data samples that are similar to those in the training data. Unlike traditional AI models that are trained to recognize patterns and make predictions, generative AI models have the ability to create entirely new data based on the patterns they have learned. This is achieved through techniques such as generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer architectures, among others.
Generative AI Use Cases and Applications.pdf
Generative AI Use Cases and Applications.pdf
alexjohnson7307
Discover the top CodeIgniter development companies that can elevate your project to new heights. Our blog explores the best firms known for their expertise in CodeIgniter framework development. From robust web applications to scalable solutions, these companies deliver excellence. Whether you're a startup or an enterprise, find the perfect match for your development needs on Top CSS Gallery's blog.
Top 10 CodeIgniter Development Companies
Top 10 CodeIgniter Development Companies
TopCSSGallery
In the ever-evolving landscape of data management, Zero-ETL is an approach that is reshaping how businesses handle and integrate their data. This webinar explores Zero-ETL, a paradigm shift from the traditional Extract, Transform, Load (ETL) process, offering a more streamlined, efficient, and real-time data integration method. We will begin with an introduction to the concept of Zero-ETL, including how it allows direct access to data in its native environment and real-time data transformation, providing up-to-date information with significantly reduced data redundancy. Next, we'll take you through several demonstrations showing how Zero-ETL can deliver real-time data and enable the free movement of data between systems. We will also discuss the various tools that support all aspects of Zero-ETL, providing attendees with an understanding of how they can adopt this innovative approach in their organizations. Lastly, the session will conclude with an interactive Q&A segment, allowing participants to gain deeper insights into how Zero-ETL can be tailored to their specific business needs and how they can get started today. Join us to discover how Zero-ETL can elevate your organization's data strategy.
The Zero-ETL Approach: Enhancing Data Agility and Insight
The Zero-ETL Approach: Enhancing Data Agility and Insight
Safe Software
This our Twelfth semiannual report on the global Cryptocurrency mining industry. Bitcoin is the world’s largest special purpose supercomputer. And it is globally decentralized. Millions of nodes all run the same open-source code to secure the Bitcoin network, create value, and put new transactions onto the distributed ledger. The latest Top500 list has just been announced at the ISC 2024 conference in Hamburg, and once again the Frontier supercomputer with 1.2 Exaflops peak performance is number one on the list. If assigned to SHA-256 hashing, Frontier would provide only the equivalent hash rate of about three cabinets of the latest high-end Bitcoin mining systems, costing less than 0.1% of Frontier’s cost. Michael Saylor, Chairman of MicroStrategy, has pointed out that GPUs are two orders of magnitude slower than the 5-nanometer technology of custom ASICs used for Bitcoin mining today. He makes the point that the Bitcoin network is unassailable by all of the hyperscale computing resources combined in AWS, Google, and Microsoft Azure cloud data centers today.
TopCryptoSupers 12thReport OrionX May2024
TopCryptoSupers 12thReport OrionX May2024
Stephen Perrenod
This webinar showcased the Loads Analysis capabilities within IESVE software.
Using IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & Ireland
IES VE
Ruby has a lot of standard libraries from Ruby 1.8. I promote them democratically with GitHub today via default and bundled gems. So, I'm working to extract them for Ruby 3.4 continuously and future versions. It's long journey for me. After that, some versions may suddenly happen LoadError at require when running bundle exec or bin/rails, for example matrix or net-smtp. We need to learn what's difference default/bundled gems with standard libraries. In this presentation, I will introduce what's the difficult to extract bundled gems from default gems and the details of the functionality that Ruby's require and bundle exec with default/bundled gems. You can learn how handle your issue about standard libraries.
Long journey of Ruby Standard library at RubyKaigi 2024
Long journey of Ruby Standard library at RubyKaigi 2024
Hiroshi SHIBATA
FIDO Seminar RSAC 2024
Hyatt driving innovation and exceptional customer experiences with FIDO passw...
Hyatt driving innovation and exceptional customer experiences with FIDO passw...
FIDO Alliance
FIDO Taipei Workshop: Securing the Edge with FDO
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
FIDO Alliance
Portal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russe
中 央社
How WebAssembly can be used to optimize and accelerate Large Language Models Inference in the Cloud.
WebAssembly is Key to Better LLM Performance
WebAssembly is Key to Better LLM Performance
Samy Fodil
Webinar Recording: https://www.panagenda.com/webinars/alles-neu-macht-der-mai-wir-durchleuchten-den-verbesserten-notes-eigenschaftendialog/ Haben Sie sich schon einmal über den zu kleinen Eigenschaftendialog in Notes geärgert? Mussten Sie einen Agenten oder eine Aktion erstellen, um schnell mal ein Feld zu ändern? Haben Sie jedes mal endlos nach dem zu vergleichenden Feld gesucht, nachdem Sie ein neues Dokument ausgewählt haben? Wollten Sie das verdammte Ding einfach nur größer machen? Zum Glück gibt es dafür eine Lösung – und sie ist wahrscheinlich bereits installiert! Mit dem kostenlosen panagenda Document Properties (Pro) erhalten Sie den Eigenschaftendialog, den Sie schon immer haben wollten. Größer, anpassbar, und im Volltext durchsuchbar. Sehen Sie mehrere Dokumente gleichzeitig oder vergleichen Sie mit einem Diff-Viewer. Ändern Sie beliebige Felder und haben Sie endlich eine einfache Möglichkeit, Profildokumente für alle Benutzer zu verwalten. Entdecken Sie mit HCL Ambassador Marc Thomas, wie Document Properties Ihre Arbeit vereinfachen und Sie bei der täglichen Verwendung von Domino-Anwendungen unterstützen kann – im Client oder im Designer. Sie werden es nicht bereuen! Für Sie in diesem Webinar - Was Document Properties ist, welche Editionen es gibt und wo es in Notes und Domino Designer zu finden ist - Wie Sie nach einem beliebigen Feld suchen und es bearbeiten, Dokumente vergleichen oder alle Daten per CSV exportieren können - Suchen, Bearbeiten und auch Löschen von Profildokumenten - Welche Konfigurationseinstellungen verfügbar sind, um Funktionen anzupassen - Wie Ihre Endbenutzer davon profitieren - Sehen Sie alles in einer Live-Demo
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
panagenda
FIDO Taipei Workshop: Securing the Edge with FDO
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
FIDO Alliance
At Skynet Technologies, our team of accessibility experts performs automated, semi-automated, and manual audits of websites and web applications as per WCAG 2.2 level AA, ADA, and section 508. Based on evaluations of the accessibility compliance level of the website’s UI, design, source code, navigation, interactive elements, and overall usability, we will provide a digital accessibility evaluation report with in-depth details of potential accessibility barriers and remediation recommendations. Get a manual website WCAG audit (2.0, 2.1, 2.2 level AA) for a small website: 10 pages: $2,500 within 7 business days 30 pages: $7,500 within 14 business days 50 pages: $12,500 within 28 business days For medium websites: 100 pages: $25,000 within 6 weeks For larger websites or audits of all pages, please reach out hello@skynettechnologies.com.
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Skynet Technologies
FIDO Taipei Workshop: Securing the Edge with FDO
Simplified FDO Manufacturing Flow with TPMs _ Liam at Infineon.pdf
Simplified FDO Manufacturing Flow with TPMs _ Liam at Infineon.pdf
FIDO Alliance
FIDO Taipei Workshop: Securing the Edge with FDO
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
FIDO Alliance
Artificial Intelligence is referred to as machine intelligence, and it is rooted in binary codes and mathematical algorithms. It is a testament to human creativity and is capable of massive data processing, pattern recognition, and even self-learning. However, the realm of AI realm is confined.
AI mind or machine power point presentation
AI mind or machine power point presentation
yogeshlabana357357
A talk given at the DATAPLAT workshop, co-located with the IEEE ICDE conference (May 2024, Utrecht, NL). Data Provenance for Data Science is our attempt to provide a foundation to add explainability to data-centric AI. It is a prototype, with lots of work still to do.
Design and Development of a Provenance Capture Platform for Data Science
Design and Development of a Provenance Capture Platform for Data Science
Paolo Missier
BrainSell's ERP Contender Series featuring Acumatica vs. Sage Intacct.
ERP Contender Series: Acumatica vs. Sage Intacct
ERP Contender Series: Acumatica vs. Sage Intacct
BrainSell Technologies
FIDO Taipei Workshop: Securing the Edge with FDO
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
FIDO Alliance
Recently uploaded
(20)
State of the Smart Building Startup Landscape 2024!
State of the Smart Building Startup Landscape 2024!
Generative AI Use Cases and Applications.pdf
Generative AI Use Cases and Applications.pdf
Top 10 CodeIgniter Development Companies
Top 10 CodeIgniter Development Companies
The Zero-ETL Approach: Enhancing Data Agility and Insight
The Zero-ETL Approach: Enhancing Data Agility and Insight
TopCryptoSupers 12thReport OrionX May2024
TopCryptoSupers 12thReport OrionX May2024
Using IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & Ireland
Long journey of Ruby Standard library at RubyKaigi 2024
Long journey of Ruby Standard library at RubyKaigi 2024
Hyatt driving innovation and exceptional customer experiences with FIDO passw...
Hyatt driving innovation and exceptional customer experiences with FIDO passw...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
Portal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russe
WebAssembly is Key to Better LLM Performance
WebAssembly is Key to Better LLM Performance
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Simplified FDO Manufacturing Flow with TPMs _ Liam at Infineon.pdf
Simplified FDO Manufacturing Flow with TPMs _ Liam at Infineon.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
AI mind or machine power point presentation
AI mind or machine power point presentation
Design and Development of a Provenance Capture Platform for Data Science
Design and Development of a Provenance Capture Platform for Data Science
ERP Contender Series: Acumatica vs. Sage Intacct
ERP Contender Series: Acumatica vs. Sage Intacct
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
Data Formats
1.
How I Turned
to the Dark Side. Formats of Data Transfer
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
Download now