This document introduces several standards for reusing machine learning models across different programming languages, including PMML, ONNX, NNEF, and NNVM. PMML has been around since 1997 and supports a wide range of models and languages. ONNX and NNEF were created more recently in 2017 to standardize neural networks and allow models to be reused across frameworks. While several options exist, ONNX may be preferable due to its focus on ease of use and active community support across Python and R.
Ali alshehri c++_comparison between c++&pythonAliAAAlshehri
C++ was first created in 1979 under the name "C with Classes" and was not commercially released until 1985. It implements object-oriented programming using classes and allows for data abstraction. C++ is commonly used to create systems software, drivers, applications requiring direct hardware access, and video games.
Python was created by Guido van Rossum in 1991 and features dynamic typing, automatic memory management, and supports multiple programming paradigms. It emphasizes code readability and provides constructs that enable clear programming on both small and large scales. Python is often used for prototyping code later implemented in other languages.
Fluvio is an open source, cloud-native data streaming platform built using Rust for high performance and reliability. It treats streams as first-class citizens and uses WebAssembly to enable intelligent stream processing. Fluvio provides a modern data stack for real-time applications with low latency, reliability, flexibility and scalability.
This project uses the ANTLR tool to convert .brf files containing MathML ASCII code into pure MathML. ANTLR generates several files by taking the NB.g4 grammar file as a parameter. The project also explores using optical character recognition to convert Braille images to text, with one tool able to convert images and PDFs to text files with 95% accuracy using pre-trained data files for languages like English, Dutch, and Spanish. The process for adding new language data files is described.
This document provides an overview of OpenCL, a standard for parallel programming of heterogeneous systems. It discusses the evolution of computing from serial to parallel processing to take advantage of multiple cores. OpenCL aims to grow the market for parallel computing through cross-vendor portability and support for diverse applications. The key aspects covered are OpenCL's objectives, architecture involving platforms, execution model and memory model, and a simple example program.
The document discusses IMPACT, a project supported by the European Community to develop a uniform technical framework for end users to work with digital library tools and applications. The framework is built on open source components and standards and uses a service-oriented architecture. It allows tools to be transformed into web services and combined into workflows for tasks like optical character recognition. The project is coordinated by the National Library of the Netherlands and evaluates workflows using datasets and ground truths.
This document discusses various programming concepts and techniques including notation, formatting data, regular expressions, programmable tools, interpreters, compilers, virtual machines, programs that write programs, using micros to generate code, and compiling on the fly. It provides examples and discusses tradeoffs between different approaches. The key idea discussed is that notation can make problems easier to solve while dynamic compilation and just-in-time compilation can provide performance benefits over interpreters or ahead-of-time compilers.
Polyglot Notebooks with Squeak/Smalltalk on the GraalVMESUG
This document discusses integrating Squeak/Smalltalk with other languages using the GraalVM. It describes how traditional approaches like foreign function interfaces and inter-process communication break the object-oriented paradigm and require significant work. The GraalVM provides a single virtual machine that supports multiple languages, allowing languages to interoperate seamlessly. The document outlines a demo of polyglot notebooks with Squeak/Smalltalk on GraalVM and references a paper with implementation details, benchmarks, and limitations. The goal is to improve language integration without sacrificing object-oriented principles and tooling.
This document introduces several standards for reusing machine learning models across different programming languages, including PMML, ONNX, NNEF, and NNVM. PMML has been around since 1997 and supports a wide range of models and languages. ONNX and NNEF were created more recently in 2017 to standardize neural networks and allow models to be reused across frameworks. While several options exist, ONNX may be preferable due to its focus on ease of use and active community support across Python and R.
Ali alshehri c++_comparison between c++&pythonAliAAAlshehri
C++ was first created in 1979 under the name "C with Classes" and was not commercially released until 1985. It implements object-oriented programming using classes and allows for data abstraction. C++ is commonly used to create systems software, drivers, applications requiring direct hardware access, and video games.
Python was created by Guido van Rossum in 1991 and features dynamic typing, automatic memory management, and supports multiple programming paradigms. It emphasizes code readability and provides constructs that enable clear programming on both small and large scales. Python is often used for prototyping code later implemented in other languages.
Fluvio is an open source, cloud-native data streaming platform built using Rust for high performance and reliability. It treats streams as first-class citizens and uses WebAssembly to enable intelligent stream processing. Fluvio provides a modern data stack for real-time applications with low latency, reliability, flexibility and scalability.
This project uses the ANTLR tool to convert .brf files containing MathML ASCII code into pure MathML. ANTLR generates several files by taking the NB.g4 grammar file as a parameter. The project also explores using optical character recognition to convert Braille images to text, with one tool able to convert images and PDFs to text files with 95% accuracy using pre-trained data files for languages like English, Dutch, and Spanish. The process for adding new language data files is described.
This document provides an overview of OpenCL, a standard for parallel programming of heterogeneous systems. It discusses the evolution of computing from serial to parallel processing to take advantage of multiple cores. OpenCL aims to grow the market for parallel computing through cross-vendor portability and support for diverse applications. The key aspects covered are OpenCL's objectives, architecture involving platforms, execution model and memory model, and a simple example program.
The document discusses IMPACT, a project supported by the European Community to develop a uniform technical framework for end users to work with digital library tools and applications. The framework is built on open source components and standards and uses a service-oriented architecture. It allows tools to be transformed into web services and combined into workflows for tasks like optical character recognition. The project is coordinated by the National Library of the Netherlands and evaluates workflows using datasets and ground truths.
This document discusses various programming concepts and techniques including notation, formatting data, regular expressions, programmable tools, interpreters, compilers, virtual machines, programs that write programs, using micros to generate code, and compiling on the fly. It provides examples and discusses tradeoffs between different approaches. The key idea discussed is that notation can make problems easier to solve while dynamic compilation and just-in-time compilation can provide performance benefits over interpreters or ahead-of-time compilers.
Polyglot Notebooks with Squeak/Smalltalk on the GraalVMESUG
This document discusses integrating Squeak/Smalltalk with other languages using the GraalVM. It describes how traditional approaches like foreign function interfaces and inter-process communication break the object-oriented paradigm and require significant work. The GraalVM provides a single virtual machine that supports multiple languages, allowing languages to interoperate seamlessly. The document outlines a demo of polyglot notebooks with Squeak/Smalltalk on GraalVM and references a paper with implementation details, benchmarks, and limitations. The goal is to improve language integration without sacrificing object-oriented principles and tooling.
ModelWriter Presentation International 01-07-2015Ferhat Erata
The project envisions an integrated authoring environment called "ModelWriter" for Technical Authors (such as Software or Systems Engineers etc.) which will combine a Semantic Word Processor (= the "Writer" part), looking like a usual word processor but capable to "understand" pieces of text and transparently create models of contents out of them; and a Knowledge Capture Tool (= the "Model" part), looking like familiar information modelling tools such as UML, BPMN, ReqIF, etc. ModelWriter will allow Technical Authors to freely move bi-directionally and interactively between text and model to enhance the quality (consistency and completeness) of the technical documents.
C++ is a general purpose programming language that runs programs using memor...hwbloom460000
C++ is a general purpose programming
language that runs programs using memory management. Two operating system
environments are commonly used in compiling, building and executing C++
applications. These are the windows and UNIX / Linux (or some UNIX / Linux
derivative) operating system.
For this assignment you will research the
following eight (8) topics and explore the implementation of memory management,
processes and threads. Each topic will be approximately one page long.
Write a seven to ten (7-10) page paper in which you:
Explain and expand on the eight (8) research topics provided. Your paper
should provide research into each of the topics.
1. Demonstrate a comprehensive knowledge of each of the eight (8) research topics.
2. Demonstrate an in-depth knowledge of the technical details of each of the eight (8) research topics.
an example may be useful. For example, when you work on the research topic of
Heap memory and allocating a memory block, you should at least demonstrate that
you understand how a memory allocator finds memory for newly created objects and
how it employs the new operator in doing this. You could expand by relating how
the memory allocator provides addressing information to the location of objects
created with the new operator. Note: When you provide an example of this code
for topic three below, ensure that you show that you understand the operations
of the new and delete operators as they relate to the memory
allocation.
3. Provide an example of C++ code that demonstrates your
understanding of the eight topics.
4. Use at least ten (10) quality resources
in this assignment. Note: Wikipedia and similar Websites do not qualify as
quality resources.
Your assignment must follow these formatting
requirements:
margins on all sides; citations and references must follow APA or
school-specific format. Check with your professor for any additional
instructions.
This document discusses managing electronic resources using linked data. It proposes developing a technical solution to convert relevant data into linked data through a data management platform, aggregate the data in a unified triplestore, and access/manipulate it via a generic GUI built on OntoWiki. The application aims to provide a flexible electronic resource management system by reusing existing vocabularies and defining new properties following ERMI guidelines. It will be open source and developed through an official OntoWiki repository in partnership between Leipzig University Library, SLUB Dresden, AKSW, and InfAI.
The document compares several meta-metamodeling languages including ARIS, Ecore, GOPPRR, GME, MS DSL Tools, and MS Visio. It finds that while object type, relation type, and attribute are core concepts supported by all languages, relation types can be realized in different ways. The analysis also observes some languages like GOPPRR and GME have greater practical expressiveness while others such as Visio are more limited. Future work could improve the comparison criteria, include more meta-metamodeling languages, and study model interoperability through transformations between meta-modeling concepts.
In this powerpoint presentation you can learn about history of python programming, Features, Strengths, Applications and careers related to the python programming and also describe what global leaders use python programming
The document summarizes a study on the interoperability between 20 meta-modeling tools. It found that while some tools support importing models from Microsoft Visio, there is no common structure or format for general model exchange between tools. Only a few tools support transformation-based exchange using simple mappings, and just two tools allow exchange at the language level by importing Visio models along with their stencils. Overall, the degree of interoperability between the meta-modeling tools is low. The study concludes more work is needed to develop mapping-based exchange of models between meta-modeling tools.
Mapping-Based Exchange of Models between Meta-Modeling Toolsheigoo
This document discusses a mapping-based approach for exchanging models between different meta-modeling tools. It presents challenges with heterogeneity between tools' meta-metamodels and meta-models. The approach uses a common meta-metamodel to bridge between tools, and defines mappings between their meta-models using a graphical mapping editor and generator. An evaluation shows the approach works for a use case but has limitations and room for improving the mapping language, editor usability, and expanding to more tools.
2018 09-03 aOS Aachen - Empower your javascript with typescript - Felix BillonaOS Community
This document discusses TypeScript and its benefits. It introduces TypeScript as a typed superset of JavaScript that provides transpilation and static typings. It describes how TypeScript compiles to JavaScript and can catch errors. It highlights features like static typing, definition files, and architectural benefits. Overall, it argues that TypeScript brings more robustness, scalability, and a smooth learning curve to front-end development.
The document provides an overview of the history and evolution of various programming languages. It discusses early languages like FORTRAN, LISP, PASCAL, C, and Java. It also covers scripting languages and their uses. The document explains what Python is as a programming language - that it is interpreted, object-oriented, and high-level. It was named after Monty Python and was created by Guido van Rossum. The document then gives examples of using Python to program Minecraft by importing protein data from PDB files and using coordinates to place blocks to visualize proteins in the game.
Context sensitive help
Toolbars:
Quick access to common actions
Views:
Panels for navigating code, files,
tasks etc.
Editor:
Where code is written and edited
Console:
Output from running code
Debug Perspective:
Tools for debugging code
Project Explorer:
Navigating files and folders
Outline:
Structure of current editor
Problems:
Errors and warnings
Properties:
Details of selected item
PyDev Perspective:
Python specific tools
Run/Debug Buttons:
Run and debug code
Status Bar:
Status messages
Welcome Page:
Getting started tips
Help:
Documentation and
Come può .NET contribuire alla Data Science? Cosa è .NET Interactive? Cosa c'entrano i notebook? E Apache Spark? E il pythonismo? E Azure? Vediamo in questa sessione di mettere in ordine le idee.
This document discusses ONNX (Open Neural Network Exchange) and its integration with MLflow for model portability and deployment. It provides an overview of ONNX, describing how it allows models to be trained in one framework and deployed in another. It then discusses several companies that support ONNX, including Microsoft's use of ONNX Runtime to accelerate models across various products, AWS and Nvidia's support, and Facebook and Intel's contributions. The document ends by explaining how MLflow recently added support for the ONNX format, allowing models to be exported to and loaded from ONNX.
C# has evolved significantly over time, from version 1 through the latest version 8. Some key developments include the addition of generics, LINQ, asynchronous programming, and dynamic features. C# continues to focus on productivity and safe, efficient code with recent versions adding capabilities like nullable reference types, async streams, and ranges/indices. .NET has also evolved with improvements to performance and new functionality in versions like .NET Core 2.1. Looking ahead, .NET Core 3 will add support for desktop frameworks like WinForms and WPF.
The document announces the XSharp Project, an open source XBase language for .NET. XSharp will consist of a compiler that supports multiple XBase dialects, runtime libraries, and Visual Studio integration. It is being created by former Vulcan.NET developers to address limitations in Vulcan and provide an open source migration path for XBase developers to .NET. XSharp will be released in stages, with an initial core dialect release and support for additional dialects like Visual Objects/Vulcan in 2016. The runtime components will be open source while compiler/IDE source requires a paid subscription.
This document provides an overview of C# and .NET Framework. It discusses the history and evolution of C#, its uses for applications like mobile, web and games. It describes key features of C# like being object-oriented, type safe and having a rich library. It also explains components of .NET Framework like Common Language Runtime, Framework Class Library and Garbage Collector. It introduces Visual Studio as an integrated development environment for C# development.
This document provides an overview of C# and .NET Framework. It discusses the history and features of C#, how it is based on C++ and Java but with additional extensions. It also summarizes the components of .NET Framework including Common Language Runtime, Framework Class Library, Common Intermediate Language, Garbage Collector, and Just-In-Time Compiler. Finally, it briefly introduces Visual Studio as an integrated development environment for C# development.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2018-embedded-vision-summit-trevett
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Neil Trevett, President of the Khronos Group and Vice President at NVIDIA, presents the "APIs for Accelerating Vision and Inferencing: Options and Trade-offs" tutorial at the May 2018 Embedded Vision Summit.
The landscape of SDKs, APIs and file formats for accelerating inferencing and vision applications continues to rapidly evolve. Low-level compute APIs, such as OpenCL, Vulkan and CUDA are being used to accelerate inferencing engines such as OpenVX, CoreML, NNAPI and TensorRT. Inferencing engines are being fed via neural network file formats such as NNEF and ONNX. Some of these APIs, like OpenCV, are vision-specific, while others, like OpenCL, are general-purpose. Some engines, like CoreML and TensorRT, are supplier-specific, while others, such as OpenVX, are open standards that any supplier can adopt. Which ones should you use for your project?
In this presentation, Trevett presents the current landscape of APIs, file formats and SDKs for inferencing and vision acceleration, explaining where each one fits in the development flow. Trevett also highlights where these APIs overlap and where they complement each other, and previews some of the latest developments in these APIs.
W1-Presentation-Introduction to Computing and Programming.pdfJarellScott
The document discusses several popular programming languages - JavaScript, Java, Python, Ruby, PHP, C++, C#, Go, Shell, and Objective-C. For each language, it provides the characteristics and creator. The languages discussed include scripting languages, object-oriented languages, and languages used for web, mobile and application development. It serves as an introduction to various programming languages for a computing course.
dotnetconf 2020 è andato e ci ha lasciato .NET 5. Ovvero una delle più importanti release di .NET di sempre. Cosa significa per il nostro lavoro? Scopriamolo assieme
ModelWriter Presentation International 01-07-2015Ferhat Erata
The project envisions an integrated authoring environment called "ModelWriter" for Technical Authors (such as Software or Systems Engineers etc.) which will combine a Semantic Word Processor (= the "Writer" part), looking like a usual word processor but capable to "understand" pieces of text and transparently create models of contents out of them; and a Knowledge Capture Tool (= the "Model" part), looking like familiar information modelling tools such as UML, BPMN, ReqIF, etc. ModelWriter will allow Technical Authors to freely move bi-directionally and interactively between text and model to enhance the quality (consistency and completeness) of the technical documents.
C++ is a general purpose programming language that runs programs using memor...hwbloom460000
C++ is a general purpose programming
language that runs programs using memory management. Two operating system
environments are commonly used in compiling, building and executing C++
applications. These are the windows and UNIX / Linux (or some UNIX / Linux
derivative) operating system.
For this assignment you will research the
following eight (8) topics and explore the implementation of memory management,
processes and threads. Each topic will be approximately one page long.
Write a seven to ten (7-10) page paper in which you:
Explain and expand on the eight (8) research topics provided. Your paper
should provide research into each of the topics.
1. Demonstrate a comprehensive knowledge of each of the eight (8) research topics.
2. Demonstrate an in-depth knowledge of the technical details of each of the eight (8) research topics.
an example may be useful. For example, when you work on the research topic of
Heap memory and allocating a memory block, you should at least demonstrate that
you understand how a memory allocator finds memory for newly created objects and
how it employs the new operator in doing this. You could expand by relating how
the memory allocator provides addressing information to the location of objects
created with the new operator. Note: When you provide an example of this code
for topic three below, ensure that you show that you understand the operations
of the new and delete operators as they relate to the memory
allocation.
3. Provide an example of C++ code that demonstrates your
understanding of the eight topics.
4. Use at least ten (10) quality resources
in this assignment. Note: Wikipedia and similar Websites do not qualify as
quality resources.
Your assignment must follow these formatting
requirements:
margins on all sides; citations and references must follow APA or
school-specific format. Check with your professor for any additional
instructions.
This document discusses managing electronic resources using linked data. It proposes developing a technical solution to convert relevant data into linked data through a data management platform, aggregate the data in a unified triplestore, and access/manipulate it via a generic GUI built on OntoWiki. The application aims to provide a flexible electronic resource management system by reusing existing vocabularies and defining new properties following ERMI guidelines. It will be open source and developed through an official OntoWiki repository in partnership between Leipzig University Library, SLUB Dresden, AKSW, and InfAI.
The document compares several meta-metamodeling languages including ARIS, Ecore, GOPPRR, GME, MS DSL Tools, and MS Visio. It finds that while object type, relation type, and attribute are core concepts supported by all languages, relation types can be realized in different ways. The analysis also observes some languages like GOPPRR and GME have greater practical expressiveness while others such as Visio are more limited. Future work could improve the comparison criteria, include more meta-metamodeling languages, and study model interoperability through transformations between meta-modeling concepts.
In this powerpoint presentation you can learn about history of python programming, Features, Strengths, Applications and careers related to the python programming and also describe what global leaders use python programming
The document summarizes a study on the interoperability between 20 meta-modeling tools. It found that while some tools support importing models from Microsoft Visio, there is no common structure or format for general model exchange between tools. Only a few tools support transformation-based exchange using simple mappings, and just two tools allow exchange at the language level by importing Visio models along with their stencils. Overall, the degree of interoperability between the meta-modeling tools is low. The study concludes more work is needed to develop mapping-based exchange of models between meta-modeling tools.
Mapping-Based Exchange of Models between Meta-Modeling Toolsheigoo
This document discusses a mapping-based approach for exchanging models between different meta-modeling tools. It presents challenges with heterogeneity between tools' meta-metamodels and meta-models. The approach uses a common meta-metamodel to bridge between tools, and defines mappings between their meta-models using a graphical mapping editor and generator. An evaluation shows the approach works for a use case but has limitations and room for improving the mapping language, editor usability, and expanding to more tools.
2018 09-03 aOS Aachen - Empower your javascript with typescript - Felix BillonaOS Community
This document discusses TypeScript and its benefits. It introduces TypeScript as a typed superset of JavaScript that provides transpilation and static typings. It describes how TypeScript compiles to JavaScript and can catch errors. It highlights features like static typing, definition files, and architectural benefits. Overall, it argues that TypeScript brings more robustness, scalability, and a smooth learning curve to front-end development.
The document provides an overview of the history and evolution of various programming languages. It discusses early languages like FORTRAN, LISP, PASCAL, C, and Java. It also covers scripting languages and their uses. The document explains what Python is as a programming language - that it is interpreted, object-oriented, and high-level. It was named after Monty Python and was created by Guido van Rossum. The document then gives examples of using Python to program Minecraft by importing protein data from PDB files and using coordinates to place blocks to visualize proteins in the game.
Context sensitive help
Toolbars:
Quick access to common actions
Views:
Panels for navigating code, files,
tasks etc.
Editor:
Where code is written and edited
Console:
Output from running code
Debug Perspective:
Tools for debugging code
Project Explorer:
Navigating files and folders
Outline:
Structure of current editor
Problems:
Errors and warnings
Properties:
Details of selected item
PyDev Perspective:
Python specific tools
Run/Debug Buttons:
Run and debug code
Status Bar:
Status messages
Welcome Page:
Getting started tips
Help:
Documentation and
Come può .NET contribuire alla Data Science? Cosa è .NET Interactive? Cosa c'entrano i notebook? E Apache Spark? E il pythonismo? E Azure? Vediamo in questa sessione di mettere in ordine le idee.
This document discusses ONNX (Open Neural Network Exchange) and its integration with MLflow for model portability and deployment. It provides an overview of ONNX, describing how it allows models to be trained in one framework and deployed in another. It then discusses several companies that support ONNX, including Microsoft's use of ONNX Runtime to accelerate models across various products, AWS and Nvidia's support, and Facebook and Intel's contributions. The document ends by explaining how MLflow recently added support for the ONNX format, allowing models to be exported to and loaded from ONNX.
C# has evolved significantly over time, from version 1 through the latest version 8. Some key developments include the addition of generics, LINQ, asynchronous programming, and dynamic features. C# continues to focus on productivity and safe, efficient code with recent versions adding capabilities like nullable reference types, async streams, and ranges/indices. .NET has also evolved with improvements to performance and new functionality in versions like .NET Core 2.1. Looking ahead, .NET Core 3 will add support for desktop frameworks like WinForms and WPF.
The document announces the XSharp Project, an open source XBase language for .NET. XSharp will consist of a compiler that supports multiple XBase dialects, runtime libraries, and Visual Studio integration. It is being created by former Vulcan.NET developers to address limitations in Vulcan and provide an open source migration path for XBase developers to .NET. XSharp will be released in stages, with an initial core dialect release and support for additional dialects like Visual Objects/Vulcan in 2016. The runtime components will be open source while compiler/IDE source requires a paid subscription.
This document provides an overview of C# and .NET Framework. It discusses the history and evolution of C#, its uses for applications like mobile, web and games. It describes key features of C# like being object-oriented, type safe and having a rich library. It also explains components of .NET Framework like Common Language Runtime, Framework Class Library and Garbage Collector. It introduces Visual Studio as an integrated development environment for C# development.
This document provides an overview of C# and .NET Framework. It discusses the history and features of C#, how it is based on C++ and Java but with additional extensions. It also summarizes the components of .NET Framework including Common Language Runtime, Framework Class Library, Common Intermediate Language, Garbage Collector, and Just-In-Time Compiler. Finally, it briefly introduces Visual Studio as an integrated development environment for C# development.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2018-embedded-vision-summit-trevett
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Neil Trevett, President of the Khronos Group and Vice President at NVIDIA, presents the "APIs for Accelerating Vision and Inferencing: Options and Trade-offs" tutorial at the May 2018 Embedded Vision Summit.
The landscape of SDKs, APIs and file formats for accelerating inferencing and vision applications continues to rapidly evolve. Low-level compute APIs, such as OpenCL, Vulkan and CUDA are being used to accelerate inferencing engines such as OpenVX, CoreML, NNAPI and TensorRT. Inferencing engines are being fed via neural network file formats such as NNEF and ONNX. Some of these APIs, like OpenCV, are vision-specific, while others, like OpenCL, are general-purpose. Some engines, like CoreML and TensorRT, are supplier-specific, while others, such as OpenVX, are open standards that any supplier can adopt. Which ones should you use for your project?
In this presentation, Trevett presents the current landscape of APIs, file formats and SDKs for inferencing and vision acceleration, explaining where each one fits in the development flow. Trevett also highlights where these APIs overlap and where they complement each other, and previews some of the latest developments in these APIs.
W1-Presentation-Introduction to Computing and Programming.pdfJarellScott
The document discusses several popular programming languages - JavaScript, Java, Python, Ruby, PHP, C++, C#, Go, Shell, and Objective-C. For each language, it provides the characteristics and creator. The languages discussed include scripting languages, object-oriented languages, and languages used for web, mobile and application development. It serves as an introduction to various programming languages for a computing course.
dotnetconf 2020 è andato e ci ha lasciato .NET 5. Ovvero una delle più importanti release di .NET di sempre. Cosa significa per il nostro lavoro? Scopriamolo assieme
The document provides an overview of the .NET framework. It describes .NET as a software platform and language-neutral runtime that executes programs written in any compliant language. It discusses key aspects of .NET including the Common Language Runtime (CLR), support for multiple programming languages, and tools like ASP.NET and Visual Studio.NET. The conclusion compares .NET to the J2EE architecture.
Difference between .net core and .net frameworkAnsi Bytecode
We are all familiar with .NET Core, .NET Framework and how they have been leading the programming world for building mobile, web-based and desktop applications. But wait, are they both same or have different infrastructure? You might be confused about both of them and probably that’s why you’re here.
The document provides an overview of using Python for bioinformatics, discussing what Python is, why it is useful for bioinformatics, how to set up Python in integrated development environments like Eclipse with PyDev, how to share code using Git and GitHub, and includes examples of Hello World and bioinformatics programs in Python. It introduces Python and argues it is well-suited for bioinformatics due to its extensive standard libraries, ease of use, and wide adoption in science. The document demonstrates how to install Python, set up an IDE, create and run simple Python programs, and use version control with Git and GitHub to collaborate on projects.
SSDN Technology is a training institute located in Delhi Gurgaon, NCR & India which offer best DotNet Training by our experienced trainer. We are providing live project training with full lab facility. For more details for a bright future call us at +91-9999-111-686.
http://www.ssdntech.com/dotnet-training.aspx
There's so much happening in the .NET ecosystem nowadays. During this session, we are going to discuss innovations which are applicable for all .NET stacks – desktop, mobile, cloud and Web. We will be talking about the new standard way of creating .NET libraries - .NET Standard, about the massive changes in the project and build sub-systems brought by Visual Studio 2017 and NuGet 4.0.
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of May 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
Do People Really Know Their Fertility Intentions? Correspondence between Sel...Xiao Xu
Fertility intention data from surveys often serve as a crucial component in modeling fertility behaviors. Yet, the persistent gap between stated intentions and actual fertility decisions, coupled with the prevalence of uncertain responses, has cast doubt on the overall utility of intentions and sparked controversies about their nature. In this study, we use survey data from a representative sample of Dutch women. With the help of open-ended questions (OEQs) on fertility and Natural Language Processing (NLP) methods, we are able to conduct an in-depth analysis of fertility narratives. Specifically, we annotate the (expert) perceived fertility intentions of respondents and compare them to their self-reported intentions from the survey. Through this analysis, we aim to reveal the disparities between self-reported intentions and the narratives. Furthermore, by applying neural topic modeling methods, we could uncover which topics and characteristics are more prevalent among respondents who exhibit a significant discrepancy between their stated intentions and their probable future behavior, as reflected in their narratives.
Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...Marlon Dumas
This webinar discusses the limitations of traditional approaches for business process simulation based on had-crafted model with restrictive assumptions. It shows how process mining techniques can be assembled together to discover high-fidelity digital twins of end-to-end processes from event data.
This presentation is about health care analysis using sentiment analysis .
*this is very useful to students who are doing project on sentiment analysis
*
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of March 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
4. A Model
“a trained model is an artefact
produced by a machine
learning algorithm as part of
training which can be used for
inference or prediction.”
8. What about .net?
• CNTK, now Microsoft Cognitive toolkit
• Januari 2017
• Linux and Windows 64bit
• Python & C#
• ONNX support (early 2018)
• Focus on NN
• Accord.net
• API
• C#
• C. R. Souza, "The Accord.NET Framework,"
• http://accord-framework.net .
• Brazil. Dec 2014.
9. Facts
It is nontrivial to switch from one AI framework to another
• Differences among the frontend and backend implementations.
• Developers often use more than one framework.
Developers need to maintain multiple backends to guarantee
performance on hardware
• ranging from smartphone chips to data center GPUs.
Chip vendors need to support multiple AI frameworks for every
new chip they build.
10. The model, independent of soft & hardware
• Type of model
• Parameters
• Target platforms
• Hardware
• Software
train run
platform
hardware
train
Model Process Trained ModelData
platform platform platform
hardwarehardware
12. Predictive Model Markup Language
• First appearance in 1997
• Last update in 2014 – version 4.3
• XML-based predictive model interchange format
• Widely accepted
• Over 30 organisations support it
• http://dmg.org/pmml/products.html
• Producers <-> consumers !
• Similar standard = PFA
14. Neural Network Exchange Format
• December 2017, version 1.0
• The Krhonos Group
• Open Specification
• Descriptive model and data
• Text based
• Detailed
• no native support yet
• exporter in C++ on Github
10/04/2018
16. Open Neural Network eXchange
• December, 2017 version 1.0
• Amazon, Facebook & Microsoft
• Many supporters are joining
• Descriptive, open format.
• ‘binary’ -> protobuf (Google - serializing structured data. )
• Working versions in Python, C# and R
10/04/2018
17. NNVM
• Amazon and University of Washingthon, first appearance oct
2017
• Non descriptive
• A compiler that translates models to a ‘uniform’ underlying
intermediate representation (IR code).
• For specific hardware (ARM, Nvidia)
18. A note on Brainscript
• Microsoft
• Is a declarative language to write models
• Part of CNTK
• Descriptive, but in a ‘binary’ format
• Future not clear…
19. Conclusion
PMML
• for all models
• broad support in different languages.
• New version on its way
ONNX and NNEF only for Neural Networks
• They both need the underlying language to be NNEF or ONNX aware
• NNEF
• More options in its current form
• Backed by a lot of companies
• But no native support yet
• ONNX
• Focusses on ease of use
• Working version in Python & R
• ... C# - requires Early adopters Win 10