This document summarizes the key topics from a lecture series on data structures and algorithms. The 12-lecture series covered fundamental data types, collections and generics, string processing, arrays and arraylists, stacks and queues, sorting algorithms, algorithm analysis and searching, recursion, binary search trees, expression trees and heaps. It emphasizes practicing programming, learning different languages, and developing algorithmic thinking to become a strong professional programmer.
Stemming And Lemmatization Tutorial | Natural Language Processing (NLP) With ...Edureka!
( **Natural Language Processing Using Python: - https://www.edureka.co/python-natural... ** )
This PPT will provide you with detailed and comprehensive knowledge of the two important aspects of Natural Language Processing ie. Stemming and Lemmatization. It will also provide you with the differences between the two with Demo on each. Following are the topics covered in this PPT:
Introduction to Big Data
What is Text Mining?
What is NLP?
Introduction to Stemming
Introduction to Lemmatization
Applications of Stemming & Lemmatization
Difference between stemming & Lemmatization
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The ever increasing need to provide a suitable derivative of a term governed by context where derivative can either stemmed word or hypernym of a word has spurred a lot of research activities in information retrieval communities. In this presentation, we are concerned with providing context centric derivatives of a term which can be useful in any search engine for obtaining better search results. Personalized Terms Derivative (PTD) provides derivative of terms based on the context surrounding the term. We also emphasize how the PTD (Personalized Terms Derivative) provides greater capabilities or enhance capabilities of an existing search engine like Solr and Elastic Search to perform boolean search effectively.
This problem is a vital cog in the wheel of text analytics world. It can also be extended to improvise the result of keyword extraction, abstractive summarization, and POS parser tree.
Exploring Patterns of Darkling Beetle Distributions in the Genus EleodesMAndrewJ
This talk, given at the 2016 International Congress of Entomology in Orlando, is about using specimen data to explore and understand patterns of present and historical distributions of the darkling beetles in the genus Eleodes Eschscholtz.
Stemming And Lemmatization Tutorial | Natural Language Processing (NLP) With ...Edureka!
( **Natural Language Processing Using Python: - https://www.edureka.co/python-natural... ** )
This PPT will provide you with detailed and comprehensive knowledge of the two important aspects of Natural Language Processing ie. Stemming and Lemmatization. It will also provide you with the differences between the two with Demo on each. Following are the topics covered in this PPT:
Introduction to Big Data
What is Text Mining?
What is NLP?
Introduction to Stemming
Introduction to Lemmatization
Applications of Stemming & Lemmatization
Difference between stemming & Lemmatization
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
The ever increasing need to provide a suitable derivative of a term governed by context where derivative can either stemmed word or hypernym of a word has spurred a lot of research activities in information retrieval communities. In this presentation, we are concerned with providing context centric derivatives of a term which can be useful in any search engine for obtaining better search results. Personalized Terms Derivative (PTD) provides derivative of terms based on the context surrounding the term. We also emphasize how the PTD (Personalized Terms Derivative) provides greater capabilities or enhance capabilities of an existing search engine like Solr and Elastic Search to perform boolean search effectively.
This problem is a vital cog in the wheel of text analytics world. It can also be extended to improvise the result of keyword extraction, abstractive summarization, and POS parser tree.
Exploring Patterns of Darkling Beetle Distributions in the Genus EleodesMAndrewJ
This talk, given at the 2016 International Congress of Entomology in Orlando, is about using specimen data to explore and understand patterns of present and historical distributions of the darkling beetles in the genus Eleodes Eschscholtz.
Palestrante: Etéocles da Silva Cavalcanti
Não é um assunto novo e nem uma novidade, mas ... modelos de filas são ferramentas importantes para os profissionais que atuam na área de Capacity Planning e estão cada vez mais inseridos em muitos produtos e ferramentas, mas ... quando modelos analíticos estão disponíveis para serem utilizados, tornam-se um problema sério pelo fato de há uma barreira quanto do seu uso e seus resultados, normalmente por falta de conhecimento, conceitos, premissas, métricas estatísticas e sobre os modelos. Esse assunto realmente tem uma complexidade teórica estatística muito alta e se entramos nos detalhes teóricos passamos a temer sobre seu uso e resultados. O objetivo é apresentar de uma forma simples e direta que modelagem analítica é ainda uma ferramenta importante e que devemos e podemos utilizá-la melhor se tivermos conhecimento melhor do seu uso e seus resultados. A simples construção de ferramentas que calcule todas as métricas estatísticas dos componentes de um sistema de fila, gera a oportunidade de realizarmos simulações com pequenas mudanças de parâmetros. Nos estudos de capacidade a utilização de teoria das filas passam a ter mais consistência e sua flexibilidade nas análises e/ou questionamentos complexos trazem respostas rápidas e consistentes aos nossos gestores na tomada de decisão.
It is a powerpoint presentation that discusses about the lesson or topic: Linear and Non-Linear Text. It also includes the differences between the types and characteristics of Linear and Non-Linear Text.
This was presented as the closing keynote at the MobileX Conference in Nashville. This presentation explains why it's a great time to be in mobile and goes over various stats about the current state of mobile.
Invited talk at Processing ROmanian in Multilingual, Interoperational and Scalable Environments (PROMISE 2010) on how to port the QALL-ME framework to a new language
ICC/Decision Services...Beyond Customer Service...What Mystery Shopping Can D...Twig Lane Group, LLC
ICC/Decision Services discuss the many uses for Mystery Shopping-Secret Shopper programs. Often misunderstood due to poor program design and execution, mystery shopping is a powerful tool to measure the customer experience in an obective manner.
Online Hyperparameter Meta-Learning with Hypergradient DistillationMLAI2
Many gradient-based meta-learning methods assume a set of parameters that do not participate in inner-optimization, which can be considered as hyperparameters. Although such hyperparameters can be optimized using the existing gradient-based hyperparameter optimization (HO) methods, they suffer from the following issues. Unrolled differentiation methods do not scale well to high-dimensional hyperparameters or horizon length, Implicit Function Theorem (IFT) based methods are restrictive for online optimization, and short horizon approximations suffer from short horizon bias. In this work, we propose a novel HO method that can overcome these limitations, by approximating the second-order term with knowledge distillation. Specifically, we parameterize a single Jacobian-vector product (JVP) for each HO step and minimize the distance from the true second-order term. Our method allows online optimization and also is scalable to the hyperparameter dimension and the horizon length. We demonstrate the effectiveness of our method on two different meta-learning methods and three benchmark datasets.
Palestrante: Etéocles da Silva Cavalcanti
Não é um assunto novo e nem uma novidade, mas ... modelos de filas são ferramentas importantes para os profissionais que atuam na área de Capacity Planning e estão cada vez mais inseridos em muitos produtos e ferramentas, mas ... quando modelos analíticos estão disponíveis para serem utilizados, tornam-se um problema sério pelo fato de há uma barreira quanto do seu uso e seus resultados, normalmente por falta de conhecimento, conceitos, premissas, métricas estatísticas e sobre os modelos. Esse assunto realmente tem uma complexidade teórica estatística muito alta e se entramos nos detalhes teóricos passamos a temer sobre seu uso e resultados. O objetivo é apresentar de uma forma simples e direta que modelagem analítica é ainda uma ferramenta importante e que devemos e podemos utilizá-la melhor se tivermos conhecimento melhor do seu uso e seus resultados. A simples construção de ferramentas que calcule todas as métricas estatísticas dos componentes de um sistema de fila, gera a oportunidade de realizarmos simulações com pequenas mudanças de parâmetros. Nos estudos de capacidade a utilização de teoria das filas passam a ter mais consistência e sua flexibilidade nas análises e/ou questionamentos complexos trazem respostas rápidas e consistentes aos nossos gestores na tomada de decisão.
It is a powerpoint presentation that discusses about the lesson or topic: Linear and Non-Linear Text. It also includes the differences between the types and characteristics of Linear and Non-Linear Text.
This was presented as the closing keynote at the MobileX Conference in Nashville. This presentation explains why it's a great time to be in mobile and goes over various stats about the current state of mobile.
Invited talk at Processing ROmanian in Multilingual, Interoperational and Scalable Environments (PROMISE 2010) on how to port the QALL-ME framework to a new language
ICC/Decision Services...Beyond Customer Service...What Mystery Shopping Can D...Twig Lane Group, LLC
ICC/Decision Services discuss the many uses for Mystery Shopping-Secret Shopper programs. Often misunderstood due to poor program design and execution, mystery shopping is a powerful tool to measure the customer experience in an obective manner.
Online Hyperparameter Meta-Learning with Hypergradient DistillationMLAI2
Many gradient-based meta-learning methods assume a set of parameters that do not participate in inner-optimization, which can be considered as hyperparameters. Although such hyperparameters can be optimized using the existing gradient-based hyperparameter optimization (HO) methods, they suffer from the following issues. Unrolled differentiation methods do not scale well to high-dimensional hyperparameters or horizon length, Implicit Function Theorem (IFT) based methods are restrictive for online optimization, and short horizon approximations suffer from short horizon bias. In this work, we propose a novel HO method that can overcome these limitations, by approximating the second-order term with knowledge distillation. Specifically, we parameterize a single Jacobian-vector product (JVP) for each HO step and minimize the distance from the true second-order term. Our method allows online optimization and also is scalable to the hyperparameter dimension and the horizon length. We demonstrate the effectiveness of our method on two different meta-learning methods and three benchmark datasets.
Research data management for medical data with pyradigm.
Python data structure for biomedical data to manage multiple tables linked via patient info or other washable IDs. Allowing continuous validation, this data structure would improve ease of use as well as integrity of the dataset.
Getting started on your natural language processing project? First you'll need to extract some features from your corpus. Frequency, Syntax parsing, word vectors are good ones to start with.
Delivered at the European Patent Office's Patent Information Conference.
November 11th 2015
Miami, Florida.
In this talk, we talk about recent advances in MT for patents and introduce our IPTranslator.com application for on-demand translation.
This presentation was provided by William Mattingly of the Smithsonian Institution, for the eight and final session of NISO's 2023 Training Series on Text and Data Mining. Session eight, "Building Data Driven Applications" was held on Thursday, December 7, 2023.
Delivered at the European Patent Office's annual Patent Information Conference (EPOPIC 2014)
November 5th 2014
Warsaw, Poland.
In this talk, we give an introduction as to how machine translation works and what makes certain content types and languages more difficult than others.
Big Data Spain 2017 - Deriving Actionable Insights from High Volume Media St...Apache OpenNLP
Media analysts have to deal with with analyzing high volumes of real-time news feeds and social media streams which is often a tedious process because they need to write search profiles for entities. Python tools like NLTK do not scale to large production data sets and cannot be plugged into a distributed scalable frameworks like Apache Flink. Apache Flink being a streaming first engine is ideally suited for ingesting multiple streams of news feeds, social media, blogs etc.. and for being able to do streaming analytics on the various feeds. Natural Language Processing tools like Apache OpenNLP can be plugged into Flink streaming pipelines so as to be able to perform common NLP tasks like Named Entity Recognition (NER), Chunking, and text classification. In this talk, we’ll be building a real-time media analyzer which does Named Entity Recognition (NER) on the individual incoming streams, calculates the co-occurrences of the named entities and aggregates them across multiple streams; index the results into a search engine and being able to query the results for actionable insights. We’ll also be showing as to how to handle multilingual documents for calculating co-occurrences. NLP practitioners will come away from this talk with a better understanding of how the various Apache OpenNLP components can help in processing large streams of data feeds and can easily be plugged into a highly scalable and distributed framework like Apache Flink.
Natural Language Processing in Artificial Intelligence - Codeup #5 - PayU Artivatic.ai
This is workshop presentation for usages for NLP in Artificial Intelligence.
This is prepared by Artivatic Data Labs.
For more info for the detailed product, visit at www.artivatic.com
Overview of the different data models, mainly: flat file, hierarchical, network, relational, and object-oreitned. CAP theorem, NoSQL major four models: Document-oriented, Column-oriented, Key-Value store, and Graph. Followed by an overview of some of the famous no-sql products: Redis, Cassandra, MongoDB, and Neo4j.
My Presentation about EMC Academic Alliance Program at Mansoura University. In this presentation, I tried to present an introduction on the most four famous EMC courses, and an overlook on the most EMC famous products.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
3. Conclusion
! Where have we been?
! What have we learned?
! Why we have taken this path?
! Where to go from here?
4. we be en?
h ere h ave
W ham El
-Ghareeb
– Dr.Hait
Final L ecture
5. Fact 1
! 2nd year Faculty of Computers Student:
! Loves Programming, Hopefully!
! Doesn’t know about Programming!
! Hates Programming!
6. Data Structures and Algorithms
! Programming Language Independent
! C# and Java are the most widely used
Programming Languages
! They are most likely similar
! We have chosen C# as you might be familiar
! We have introduced Python for Novice
7. Fact 2
! 2nd Year Faculty of Computers Student:
! Doesn’t Read / Research
! Doesn’t Write Code
! Doesn’t Co-operate with each other
8. Data Structures and Algorithms
! Delivery of Reports (one or two)
! Delivery of Projects, as Bonus
! Providing Lecture Notes online
! Study Groups
! Student of the Week
9. Fact 3
! 2nd Year Faculty of Computers Student:
! Not used to ‘expressive’ ‘open ended’ questions
11. learn ed?
t have we
Wha -Ghareeb
ham El
– Dr.Hait
Final L ecture
12. L ectu res?
How Many hareeb
-G
ham El
– Dr.Hait
Final L ecture
13. 2 Lect ures
1
-Ghareeb
ham El
– Dr.Hait
Final L ecture
14. L e c ture 1
-Ghareeb
ham El
– Dr.Hait
Final L ecture
15. Topics
! Welcome to Data Structures and Algorithms
! Importance of the Subject
! Recipe to be a Programmer:
! 10K + Hours
! Peter Norvig
16. L e c ture 2
-Ghareeb
ham El
– Dr.Hait
Final L ecture
17. Programming Languages are
Not the Same
! Different Programming Language Categories
! 19 Different Topics for Comparison
! C#, Java, C++ They are the same!
! Quick intro to C#
18. L e c ture 3
-Ghareeb
ham El
– Dr.Hait
Final L ecture
19. Collections and Generics
! Slideshare mentioned your access, Thank You J
! Collections and Collection Types
! Collection Properties and Methods
! Generics
! Evaluating Data Structures Performance
! Chart
20. L e c ture 4
-Ghareeb
ham El
– Dr.Hait
Final L ecture
21. String Theory
! Strings are Collections
! Strings are immutable
! String and string are equivalent
! Strings are Reference Types
! Strings are Nullable
! Strings have built-in Methods and Properties
22. L e c ture 5
-Ghareeb
ham El
– Dr.Hait
Final L ecture
23. Arrays and Arraylists
! Array is Class
! Arrays are indexed collections of data
! Vector, Multidimensional, Parameter, Jagged
! Arraylist is an Array that grows Dynamically
! Arraylist Properties and Methods
! Memory Management of Arrays
24. L e c ture 6
-Ghareeb
ham El
– Dr.Hait
Final L ecture
25. Stacks and Queues
! LIFO vs. FIFO
! Programming Languages vs. Operating Systems
! Push, Pop, Peek, Count
! Enqueue, Dequeue, Count
! Operations, Properties, Remarks
26. L e c ture 7
-Ghareeb
ham El
– Dr.Hait
Final L ecture
27. Basic Comparison Sort
! Sorting
! Order Theory
! Weak, Standard Order
! Sorting Algorithm
! Bubble, Selection, Insertion Sort
28. L e c ture 8
-Ghareeb
ham El
– Dr.Hait
Final L ecture
29. Algorithm Analysis
Searching
! Algorithms, Execution Time, Complexity Analysis
! Growth Rates
! Big-O Notation
! Classes of Algorithm
! Code Evaluation
! Searching: Linear, and Binary Search
30. L e c ture 9
-Ghareeb
ham El
– Dr.Hait
Final L ecture
31. Data Structures in Python
! Crash Course ! Lists ! Set
! Numbers ! As Stacks ! Dictionaries
! As Queues
! Strings
! Functional ! Looping
! Lists Programming
! Control Flows
! Map
! Functions ! Reduce
! Coding Style ! Filter
32. cture 10
Le ham El
-Ghareeb
– Dr.Hait
Final L ecture
33. Recursion
Binary Search Tree
! Recursion: Recursive Function and Solutions
! Trees: Tree Structure
! Binary Trees
! Tree Traversals: Pre-Order, In-Order, Post-Order,
Breadth First
34. cture 11
Le ham El
-Ghareeb
– Dr.Hait
Final L ecture
36. cture 12
Le ham El
-Ghareeb
– Dr.Hait
Final L ecture
37. Conclusion
! Where have we been?
! What have we learned?
! Why we have taken this path?
! Where to go from here?
38. this Path?
ve ta ken
Why we ha hareeb
-G
ham El
– Dr.Hait
Final L ecture
39. Path
! Focusing on Basics of C# Programming
Language
! Stepping Slowly and Smoothly in Data
Structures and Algorithms
! Mixing Object Oriented Programming Language
and Interpreted Functional Programming
Language
40. Path (Cont.)
! Highlighting e-Learning and Social Networks in
Communication:
! Online Course Page
! Twitter and G+
! Reports Delivery
41. mh ere?
to G O fro
W here -Ghareeb
ham El
– Dr.Hait
Final L ecture
42. Professional Programmer
! Practice, Practice, Practice
! Keep yourself Updated
! Follow online Resources
! Become Master of One Programming Language
! Become Familiar with Different Programming
Languages
43. Algorithmic Thinking
! Focus on Programming Language independent
Techniques
! Participate in Online and Faculty Communities
! Become Partner with worldwide consortiums
! Participate in Competitions
! Read online Magazines