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CBSE Class XI New Syllabus 2018-19
11 syllabus
11 syllabus
Praveen M Jigajinni
The presentation will describe an algorithm through which one can recognize Devanagari Characters. Devanagari is the script in which Hindi is represented. This algorithm could automatically segment character from the image of Devenagari text and then recognize them. For extracting the individual characters from the image of Devanagari text, algorithm segmented the image several times using the vertical and horizontal projection. The algorithm starts with first segmenting the lines separately from the document by taking horizontal projection and then the line into words by taking vertical projection of the line. Another step which is particular to the separation of Devanagari characters was required and was done by first removing the header line by finding horizontal projection of each word. The characters can then be extracted by vertical projection of the word without the header line. Algorithm uses a Kohonen Neural Netowrk for the recognition task. After the separation of the characters from the image, the image matrix was then downsampled to bring it down to a fixed size so as to make the recognition size independent. The matrix can then be fed as input neurons to the Kohonen Neural Network and the winning neuron is found which identifies the recognized the character. This information in Kohonen Neural Network was stored earlier during the training phase of the neural network. For this, we first assigned random weights from input neurons to output neurons and then for each training set, the winning neuron was calculated by finding the maximum output produced by the neurons. The wights for this winning neuron were then adjusted so that it responds to this pattern more strongly the next time.
Devanagari Character Recognition
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https://www.irjet.net/archives/V7/i3/IRJET-V7I3741.pdf
IRJET - A Survey on Recognition of Strike-Out Texts in Handwritten Documents
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Speakers often switch back and forth between languages when speaking or writing, mostly in informal settings. This language interchanging involves complex grammar and the terms “code switching” or “code mixing” are used to describe It .
Named Entity Recognition For Hindi-English code-mixed Twitter Text
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In this part 1 presentation, I have attempted to provide a '30,000 feet view' of BERT (Bidirectional Encoder Representations from Transformer) - a state of the art Language Model in NLP with high level technical explanations. I have attempted to collate useful information about BERT from various useful sources.
BERT - Part 1 Learning Notes of Senthil Kumar
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CBSE Class XI New Syllabus 2018-19
11 syllabus
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Praveen M Jigajinni
The presentation will describe an algorithm through which one can recognize Devanagari Characters. Devanagari is the script in which Hindi is represented. This algorithm could automatically segment character from the image of Devenagari text and then recognize them. For extracting the individual characters from the image of Devanagari text, algorithm segmented the image several times using the vertical and horizontal projection. The algorithm starts with first segmenting the lines separately from the document by taking horizontal projection and then the line into words by taking vertical projection of the line. Another step which is particular to the separation of Devanagari characters was required and was done by first removing the header line by finding horizontal projection of each word. The characters can then be extracted by vertical projection of the word without the header line. Algorithm uses a Kohonen Neural Netowrk for the recognition task. After the separation of the characters from the image, the image matrix was then downsampled to bring it down to a fixed size so as to make the recognition size independent. The matrix can then be fed as input neurons to the Kohonen Neural Network and the winning neuron is found which identifies the recognized the character. This information in Kohonen Neural Network was stored earlier during the training phase of the neural network. For this, we first assigned random weights from input neurons to output neurons and then for each training set, the winning neuron was calculated by finding the maximum output produced by the neurons. The wights for this winning neuron were then adjusted so that it responds to this pattern more strongly the next time.
Devanagari Character Recognition
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Pulkit Goyal
https://www.irjet.net/archives/V7/i3/IRJET-V7I3741.pdf
IRJET - A Survey on Recognition of Strike-Out Texts in Handwritten Documents
IRJET - A Survey on Recognition of Strike-Out Texts in Handwritten Documents
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How to prepare for an interview in data structures?
Placement oriented data structures
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Lovelyn Rose
Speakers often switch back and forth between languages when speaking or writing, mostly in informal settings. This language interchanging involves complex grammar and the terms “code switching” or “code mixing” are used to describe It .
Named Entity Recognition For Hindi-English code-mixed Twitter Text
Named Entity Recognition For Hindi-English code-mixed Twitter Text
Amogh Kawle
In this part 1 presentation, I have attempted to provide a '30,000 feet view' of BERT (Bidirectional Encoder Representations from Transformer) - a state of the art Language Model in NLP with high level technical explanations. I have attempted to collate useful information about BERT from various useful sources.
BERT - Part 1 Learning Notes of Senthil Kumar
BERT - Part 1 Learning Notes of Senthil Kumar
Senthil Kumar M
This Part 2 presentation is a more in-depth view of BERT - Bidirectional Encoder Representations from Transformer. The source links offer more depth to the brief overview in the slides
BERT - Part 2 Learning Notes
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Senthil Kumar M
IOSR Journal of Computer Engineering (IOSR-JCE) vol.17 issue.1 version.1
Artificial Neural Network For Recognition Of Handwritten Devanagari Character
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The transformer is one of the most popular state-of-the-art deep (SOTA) learning architectures that is mostly used for natural language processing (NLP) tasks. Ever since the advent of the transformer, it has replaced RNN and LSTM for various tasks. The transformer also created a major breakthrough in the field of NLP and also paved the way for new revolutionary architectures such as BERT.
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Near-duplicate document detection is a well-known problem in the area of information retrieval. It is an important problem to be solved for many applications in IT industry. It has been studied with profound research literatures. This article provides a novel solution to this classic problem. We present the problem with abstract models along with additional concepts such as text models, document fingerprints and document similarity. With these concepts, the problem can be transformed into keyword like search problem with results ranked by document similarity. There are two major techniques. The first technique is to extract robust and unique fingerprints from a document. The second one is to calculate document similarity effectively. Algorithms for both fingerprint extraction and document similarity calculation are introduced as a complete solution.
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Andherson Maeda
As a data science Intern at Leapcheck Services private limited, I have developed a naive chatbot using sequence to sequence model by LSTM of RNN. Sharing the tutorial which I made explicitly for the deep learning enthusiasts to provide them a basic insight on how chatbot can be developed with the help of recurrent neural network.
Chatbot ppt
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From the existing research it has been observed that many techniques and methodologies are available for performing every step of Automatic Speech Recognition (ASR) system, but the performance (Minimization of Word Error Recognition-WER and Maximization of Word Accuracy Rate- WAR) of the methodology is not dependent on the only technique applied in that method. The research work indicates that, performance mainly depends on the category of the noise, the level of the noise and the variable size of the window, frame, frame overlap etc is considered in the existing methods. The main aim of the work presented in this paper is to use variable size of parameters like window size, frame size and frame overlap percentage to observe the performance of algorithms for various categories of noise with different levels and also train the system for all size of parameters and category of real world noisy environment to improve the performance of the speech recognition system. This paper presents the results of Signal-to-Noise Ratio (SNR) and Accuracy test by applying variable size of parameters. It is observed that, it is really very hard to evaluate test results and decide parameter size for ASR performance improvement for its resultant optimization. Hence, this study further suggests the feasible and optimum parameter size using Fuzzy Inference System (FIS) for enhancing resultant accuracy in adverse real world noisy environmental conditions. This work will be helpful to give discriminative training of ubiquitous ASR system for better Human Computer Interaction (HCI). Keywords: ASR Performance, ASR Parameters Optimization, Multi-Environmental Training, Fuzzy Inference System for ASR, ubiquitous ASR system, Human Computer Interaction (HCI)
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journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals, yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
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InftyReader is an Optical Character Recognition (OCR) application that automatically converts "inaccessible" math content such as: 1) printed textbooks containing mathematics; 2) images containing mathematics; and, 3) PDF files that containing mathematics into formats that are accessible by students with "print disabilities." These formats include LaTeX, MathML, and Word XML. A "print disability" is a condition related to blindness, visual impairment, specific learning disability or other physical condition in which the student needs an alternative or specialized format (i.e., Braille, Large Print, Audio, Digital text) in order to access and acquire knowledge from conventional print/digital materials. ChattyInfty 3 is a talking math editor. It can be used to edit files processed by InftyReader. Once editing is complete, ChattyInfty 3 can export files into a wide range of accessible formats including: 1. Spoken Text 2. DAISY 2.02 multimedia 3. DAISY 2.02 audio 4. DAISY 3 multimedia 5. DAISY 3 text (with audio for math) 6. DAISY 3 text-only 7. EPUB3 media overlays 8. EPUB3 no audio 9. EPUB3 iBooks media overlays
InftyReader and ChattyInfty Overview
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Python is a dynamic object-oriented programming language. Python provides strong support for integration with other programming languages and other tools. Python programming is rarely used in the field of artificial intelligence, especially artificial neural networks. This research focuses on running Python programming to recognize hiragana letters. In learning the character of Hiragana, one can experience difficulties because of the many combinations of vowels that form new letters by different means of reading and meaning. Discrete Hopfield network is a fully connected, that every unit is attached to every other unit. This network has asymmetrical weights. At Hopfield Network, each unit has no relationship with itself. Therefore it is expected that a computer system that can help recognize the Hiragana Images. With this pattern recognition Application of Hiragana Images, it is expected the system can be developed further to recognize the Hiragana Images quickly and precisely.
Python Application: Visual Approach of Hopfield Discrete Method for Hiragana ...
Python Application: Visual Approach of Hopfield Discrete Method for Hiragana ...
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Oak Harbor School District Tier 3 Coaching Session: Change & Resistance
Coaching Change & Resistance 3 19 10 With Notes
Coaching Change & Resistance 3 19 10 With Notes
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Adlt 610 Class 6 Fall 2007 Understanding And Dealing With Resistance
Adlt 610 Class 6 Fall 2007 Understanding And Dealing With Resistance
tjcarter
Agile 2015 Talk with Mike Lowery “They are resisting the changes I am trying to implement!” It’s a common refrain when people don’t embrace a change with the speed or enthusiasm desired. Do you keep pushing, give up or call in the big guns? How you respond to resistance can doom the change to failure, or boost the chance of success. As coaches, we introduce new ideas in many different contexts. Relying on positional authority (our role as coach), or calling on outside authority (the managers who hired us) isn't likely to get those ideas a fair hearing. In this talk, Mike and Esther will help you see resistance from a new perspective. By understanding how much influence you have, what forces are interacting around you and seeing different ways to re-frame your issues you can still get your message across without “inflicting help” on others.
Coaching Flow: Moving Past Resistance
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We hear so much about being an introvert but just knowing that isn't enough. You need to translate your personality into a competitive advantage and have strategies for where you need to adapt.
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The transformer is one of the most popular state-of-the-art deep (SOTA) learning architectures that is mostly used for natural language processing (NLP) tasks. Ever since the advent of the transformer, it has replaced RNN and LSTM for various tasks. The transformer also created a major breakthrough in the field of NLP and also paved the way for new revolutionary architectures such as BERT.
An introduction to the Transformers architecture and BERT
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Avijit Kumar
Near-duplicate document detection is a well-known problem in the area of information retrieval. It is an important problem to be solved for many applications in IT industry. It has been studied with profound research literatures. This article provides a novel solution to this classic problem. We present the problem with abstract models along with additional concepts such as text models, document fingerprints and document similarity. With these concepts, the problem can be transformed into keyword like search problem with results ranked by document similarity. There are two major techniques. The first technique is to extract robust and unique fingerprints from a document. The second one is to calculate document similarity effectively. Algorithms for both fingerprint extraction and document similarity calculation are introduced as a complete solution.
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From theory to practice
Chatbots and Deep Learning
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Andherson Maeda
As a data science Intern at Leapcheck Services private limited, I have developed a naive chatbot using sequence to sequence model by LSTM of RNN. Sharing the tutorial which I made explicitly for the deep learning enthusiasts to provide them a basic insight on how chatbot can be developed with the help of recurrent neural network.
Chatbot ppt
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Manish Mishra
From the existing research it has been observed that many techniques and methodologies are available for performing every step of Automatic Speech Recognition (ASR) system, but the performance (Minimization of Word Error Recognition-WER and Maximization of Word Accuracy Rate- WAR) of the methodology is not dependent on the only technique applied in that method. The research work indicates that, performance mainly depends on the category of the noise, the level of the noise and the variable size of the window, frame, frame overlap etc is considered in the existing methods. The main aim of the work presented in this paper is to use variable size of parameters like window size, frame size and frame overlap percentage to observe the performance of algorithms for various categories of noise with different levels and also train the system for all size of parameters and category of real world noisy environment to improve the performance of the speech recognition system. This paper presents the results of Signal-to-Noise Ratio (SNR) and Accuracy test by applying variable size of parameters. It is observed that, it is really very hard to evaluate test results and decide parameter size for ASR performance improvement for its resultant optimization. Hence, this study further suggests the feasible and optimum parameter size using Fuzzy Inference System (FIS) for enhancing resultant accuracy in adverse real world noisy environmental conditions. This work will be helpful to give discriminative training of ubiquitous ASR system for better Human Computer Interaction (HCI). Keywords: ASR Performance, ASR Parameters Optimization, Multi-Environmental Training, Fuzzy Inference System for ASR, ubiquitous ASR system, Human Computer Interaction (HCI)
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Waqas Tariq
Online reviews are a feedback to the product and play a key role in improving the product to cater to consumers. Online reviews that rely heavily on manual categorization are time consuming and labor intensive.The recurrent neural network in deep learning can process time series data, while the long and short term memory network can process long time sequence data well. This has good experimental verification support in natural language processing, machine translation, speech recognition and language model.The merits of the extracted data features affect the classification results produced by the classification model. The LDA topic model adds a priori a posteriori knowledge to classify the data so that the characteristics of the data can be extracted efficiently.Applied to the classifier can improve accuracy and efficiency. Two-way long-term and short-term memory networks are variants and extensions of cyclic neural networks.The deep learning framework Keras uses Tensorflow as the backend to build a convenient two-way long-term and short-term memory network model, which provides a strong technical support for the experiment.Using the LDA topic model to extract the keywords needed to train the neural network and increase the internal relationship between words can improve the learning efficiency of the model. The experimental results in the same experimental environment are better than the traditional word frequency features.
THE EFFECTS OF THE LDA TOPIC MODEL ON SENTIMENT CLASSIFICATION
THE EFFECTS OF THE LDA TOPIC MODEL ON SENTIMENT CLASSIFICATION
ijscai
Text Tokenization strategies leveraging ElasticSearch and Apache Lucene
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NLP techniques used for Spell checking to recommend find error in the written word and also suggest a relevant word. Algorithm: Jaccard Coefficient, The Levenshtein Distance
Spell checker using Natural language processing
Spell checker using Natural language processing
Sandeep Wakchaure
Process the sentiments of NLP with Naive Bayes Rule, Random Forest, Support Vector Machine, and much more. Thanks, for your time, if you enjoyed this short slide there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
NLP - Sentiment Analysis
NLP - Sentiment Analysis
Rupak Roy
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals, yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
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IRJET - Speech to Speech Translation using Encoder Decoder Architecture
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InftyReader and ChattyInfty Overview
InftyReader and ChattyInfty Overview
steveapps4android
BERT: Bidirectional Encoder Representation from Transformer. BERT is a Pretrained Model by Google for State of the art NLP tasks. BERT has the ability to take into account Syntaxtic and Semantic meaning of Text.
NLP State of the Art | BERT
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Python is a dynamic object-oriented programming language. Python provides strong support for integration with other programming languages and other tools. Python programming is rarely used in the field of artificial intelligence, especially artificial neural networks. This research focuses on running Python programming to recognize hiragana letters. In learning the character of Hiragana, one can experience difficulties because of the many combinations of vowels that form new letters by different means of reading and meaning. Discrete Hopfield network is a fully connected, that every unit is attached to every other unit. This network has asymmetrical weights. At Hopfield Network, each unit has no relationship with itself. Therefore it is expected that a computer system that can help recognize the Hiragana Images. With this pattern recognition Application of Hiragana Images, it is expected the system can be developed further to recognize the Hiragana Images quickly and precisely.
Python Application: Visual Approach of Hopfield Discrete Method for Hiragana ...
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Adlt 610 Class 6 Fall 2007 Understanding And Dealing With Resistance
tjcarter
Agile 2015 Talk with Mike Lowery “They are resisting the changes I am trying to implement!” It’s a common refrain when people don’t embrace a change with the speed or enthusiasm desired. Do you keep pushing, give up or call in the big guns? How you respond to resistance can doom the change to failure, or boost the chance of success. As coaches, we introduce new ideas in many different contexts. Relying on positional authority (our role as coach), or calling on outside authority (the managers who hired us) isn't likely to get those ideas a fair hearing. In this talk, Mike and Esther will help you see resistance from a new perspective. By understanding how much influence you have, what forces are interacting around you and seeing different ways to re-frame your issues you can still get your message across without “inflicting help” on others.
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We hear so much about being an introvert but just knowing that isn't enough. You need to translate your personality into a competitive advantage and have strategies for where you need to adapt.
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Lec1cgu13updated.ppt
Lec1cgu13updated.ppt
kalai75
Start with an introduction that defines data science and its scope and applications in various domains.
Lec1cgu13updated.ppt
Lec1cgu13updated.ppt
Aravind Reddy
Data Orchestration Summit 2020 organized by Alluxio https://www.alluxio.io/data-orchestration-summit-2020/ The Future of Computing is Distributed Professor Ion Stoica, UC Berkeley RISELab About Alluxio: alluxio.io Engage with the open source community on slack: alluxio.io/slack
The Future of Computing is Distributed
The Future of Computing is Distributed
Alluxio, Inc.
Brief overview of the what, why, and how of Test-Driven-Development (TDD), using PHPUnit.
Tdd in practice
Tdd in practice
Andrew Meredith
Meetup 29042015
Meetup 29042015
lbishal
author: Ivar Thorson great slide!!! congratulations.
Functional Programming with Immutable Data Structures
Functional Programming with Immutable Data Structures
elliando dias
AP COMPUTER SCIENCE PRINCIPLES
Lesson4.2 u4 l1 binary squences
Lesson4.2 u4 l1 binary squences
Lexume1
On how to change the utility curve of deep learning to make deep learning projects deliver an ROI no matter how accurate the machine learning system is - presented at the Nasscom Analytics Summit 2018.
Document Analysis with Deep Learning
Document Analysis with Deep Learning
aiaioo
Slides for BitByte conference speech. September 2013.
On being a professional software developer
On being a professional software developer
Anton Kirillov
"The workshop is designed for beginners to programming The primary target audience are students of all ages and backgrounds. Attendees in the workshop will learn the basics of the Python programming language and get help for hands-on, project-based practice. Attendees will set up a Python development environment on their own computer and complete a short project in Python."
Ardian Haxha- Flying with Python (OSCAL2014)
Ardian Haxha- Flying with Python (OSCAL2014)
Open Labs Albania
ကွန်ပျုတာအသံုးပြုခြင်းများအကြောင်း
CSC1100 - Chapter01 - Overview of Using Computers
CSC1100 - Chapter01 - Overview of Using Computers
Yhal Htet Aung
It seminar 1.0
It seminar 1.0
GiulianoVesci
On Being a Professional Software Developer
Антон Кириллов, ZeptoLab
Антон Кириллов, ZeptoLab
Diana Dymolazova
INTRODUCTION, DATA TYPES, OPERATORS, CONTROL FLOW STATEMENTS, FUNCTIONS & LAMBDA EXPRESSIONS
Python programming
Python programming
saroja20
Semelhante a Being Professional
(20)
Computing with Directed Labeled Graphs
Computing with Directed Labeled Graphs
Rrw02 Week 1 Assignment
Rrw02 Week 1 Assignment
Evolving as a professional software developer
Evolving as a professional software developer
Data Science
Data Science
Lec1cgu13updated.ppt
Lec1cgu13updated.ppt
Data science programming .ppt
Data science programming .ppt
Lec1cgu13updated.ppt
Lec1cgu13updated.ppt
Lec1cgu13updated.ppt
Lec1cgu13updated.ppt
The Future of Computing is Distributed
The Future of Computing is Distributed
Tdd in practice
Tdd in practice
Meetup 29042015
Meetup 29042015
Functional Programming with Immutable Data Structures
Functional Programming with Immutable Data Structures
Lesson4.2 u4 l1 binary squences
Lesson4.2 u4 l1 binary squences
Document Analysis with Deep Learning
Document Analysis with Deep Learning
On being a professional software developer
On being a professional software developer
Ardian Haxha- Flying with Python (OSCAL2014)
Ardian Haxha- Flying with Python (OSCAL2014)
CSC1100 - Chapter01 - Overview of Using Computers
CSC1100 - Chapter01 - Overview of Using Computers
It seminar 1.0
It seminar 1.0
Антон Кириллов, ZeptoLab
Антон Кириллов, ZeptoLab
Python programming
Python programming
Mais de Abdalla Mahmoud
Persistence
Persistence
Abdalla Mahmoud
JavaServer Pages
JavaServer Pages
Abdalla Mahmoud
Java EE Services
Java EE Services
Abdalla Mahmoud
Message Driven Beans (6)
Message Driven Beans (6)
Abdalla Mahmoud
Servlets
Servlets
Abdalla Mahmoud
Introduction to the World Wide Web
Introduction to the World Wide Web
Abdalla Mahmoud
Introduction to Java Enterprise Edition
Introduction to Java Enterprise Edition
Abdalla Mahmoud
Object-Oriented Concepts
Object-Oriented Concepts
Abdalla Mahmoud
One-Hour Java Talk
One-Hour Java Talk
Abdalla Mahmoud
Mais de Abdalla Mahmoud
(9)
Persistence
Persistence
JavaServer Pages
JavaServer Pages
Java EE Services
Java EE Services
Message Driven Beans (6)
Message Driven Beans (6)
Servlets
Servlets
Introduction to the World Wide Web
Introduction to the World Wide Web
Introduction to Java Enterprise Edition
Introduction to Java Enterprise Edition
Object-Oriented Concepts
Object-Oriented Concepts
One-Hour Java Talk
One-Hour Java Talk
Último
With real-time traffic, hazard alerts, and voice instructions, among others, launching an intuitive taxi app in Brazil is your golden ticket to entrepreneurial success. For more info visit our website : https://www.v3cube.com/uber-clone-portuguese-brazil/
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of Brazil
V3cube
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
The Digital Insurer
ICT role in 21 century education. How to ICT help in education
presentation ICT roal in 21st century education
presentation ICT roal in 21st century education
jfdjdjcjdnsjd
Presented by Sergio Licea and John Hendershot
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
ThousandEyes
Created by Mozilla Research in 2012 and now part of Linux Foundation Europe, the Servo project is an experimental rendering engine written in Rust. It combines memory safety and concurrency to create an independent, modular, and embeddable rendering engine that adheres to web standards. Stewardship of Servo moved from Mozilla Research to the Linux Foundation in 2020, where its mission remains unchanged. After some slow years, in 2023 there has been renewed activity on the project, with a roadmap now focused on improving the engine’s CSS 2 conformance, exploring Android support, and making Servo a practical embeddable rendering engine. In this presentation, Rakhi Sharma reviews the status of the project, our recent developments in 2023, our collaboration with Tauri to make Servo an easy-to-use embeddable rendering engine, and our plans for the future to make Servo an alternative web rendering engine for the embedded devices industry. (c) Embedded Open Source Summit 2024 April 16-18, 2024 Seattle, Washington (US) https://events.linuxfoundation.org/embedded-open-source-summit/ https://ossna2024.sched.com/event/1aBNF/a-year-of-servo-reboot-where-are-we-now-rakhi-sharma-igalia
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
Igalia
In this session, we will delve into strategic approaches for optimizing knowledge management within Microsoft 365, amidst the evolving landscape of Copilot. From leveraging automatic metadata classification and permission governance with SharePoint Premium, to unlocking Viva Engage for the cultivation of knowledge and communities, you will gain actionable insights to bolster your organization's knowledge-sharing initiatives. In this session, we will also explore how to facilitate solutions to enable your employees to find answers and expertise within Microsoft 365. You will leave equipped with practical techniques and a deeper understanding of how there is more to effective knowledge management than just enabling Copilot, but building actual solutions to prepare the knowledge that Copilot and your employees can use.
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Drew Madelung
The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Joaquim Jorge
Discord is a free app offering voice, video, and text chat functionalities, primarily catering to the gaming community. It serves as a hub for users to create and join servers tailored to their interests. Discord’s ecosystem comprises servers, each functioning as a distinct online community with its own channels dedicated to specific topics or activities. Users can engage in text-based discussions, voice calls, or video chats within these channels. Understanding Discord Servers Discord servers are virtual spaces where users congregate to interact, share content, and build communities. Servers may revolve around gaming, hobbies, interests, or fandoms, providing a platform for like-minded individuals to connect. Communication Features Discord offers a range of communication tools, including text channels for messaging, voice channels for real-time audio conversations, and video channels for face-to-face interactions. These features facilitate seamless communication and collaboration. What Does NSFW Mean? The acronym NSFW stands for “Not Safe For Work,” indicating content that may be inappropriate for professional or public settings. NSFW Content NSFW content encompasses material that is sexually explicit, violent, or otherwise graphic in nature. It often includes nudity, profanity, or depictions of sensitive topics.
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
UK Journal
Three things you will take away from the session: • How to run an effective tenant-to-tenant migration • Best practices for before, during, and after migration • Tips for using migration as a springboard to prepare for Copilot in Microsoft 365 Main ideas: Migration Overview: The presentation covers the current reality of cross-tenant migrations, the triggers, phases, best practices, and benefits of a successful tenant migration Considerations: When considering a migration, it is important to consider the migration scope, performance, customization, flexibility, user-friendly interface, automation, monitoring, support, training, scalability, data integrity, data security, cost, and licensing structure Next Wave: The next wave of change includes the launch of Copilot, which requires businesses to be prepared for upcoming changes related to Copilot and the cloud, and to consolidate data and tighten governance ShareGate: ShareGate can help with pre-migration analysis, configurable migration tool, and automated, end-user driven collaborative governance
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
sammart93
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
The Digital Insurer
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writing some innovation for development and search
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
sudhanshuwaghmare1
Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
Enterprise Knowledge
Details
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
vu2urc
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
The Digital Insurer
Presentation on the progress in the Domino Container community project as delivered at the Engage 2024 conference
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
Martijn de Jong
This presentation explores the impact of HTML injection attacks on web applications, detailing how attackers exploit vulnerabilities to inject malicious code into web pages. Learn about the potential consequences of such attacks and discover effective mitigation strategies to protect your web applications from HTML injection vulnerabilities. for more information visit https://bostoninstituteofanalytics.org/category/cyber-security-ethical-hacking/
HTML Injection Attacks: Impact and Mitigation Strategies
HTML Injection Attacks: Impact and Mitigation Strategies
Boston Institute of Analytics
Tech Trends Report 2024 Future Today Institute
Tech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdf
hans926745
Digital Global Overview Report 2024 Slides presentation for Event presented in 2024 after compilation of data around last year.
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
hans926745
Scaling API-first – The story of a global engineering organization Ian Reasor, Senior Computer Scientist - Adobe Radu Cotescu, Senior Computer Scientist - Adobe Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
apidays
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Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of Brazil
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
presentation ICT roal in 21st century education
presentation ICT roal in 21st century education
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
HTML Injection Attacks: Impact and Mitigation Strategies
HTML Injection Attacks: Impact and Mitigation Strategies
Tech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Being Professional
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Being Professional الباشمهندس
/ عبد الله محمود حمدي خريج علوم الحاسب – دفعة 2009 رقم الخريج : 10074142
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Virtual Memory Program
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