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    1. Machine Learning in a Flash (Extended Edition): An Introduction to Natural Language Processing and Clustering

      Machine Learning in a Flash (Extended Edition): An Introduction to Natural Language Processing and Clustering

      Published on Aug 11, 2017 Learn the basics behind machine learning, natural language processing, and clustering. In this presentation we’ll go over a handful of really quick machine learning algorithms. We’ll cover the difference between unsupervised and supervised learning in artificial intelligence, classification, clustering, and natural language processing to classify sentences as being about “eating”.

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    2. Hallyu, Not Today: Politicization of Korean Wave & Financialization of KPOP in Korean News for 16 years

      Hallyu, Not Today: Politicization of Korean Wave & Financialization of KPOP in Korean News for 16 years

      Published on Jul 31, 2017 At the end of 2016, Park Geun-hye-Choi Soon-sil gate has been a big influence on Korean society, including the impeachment of the president. One of the core suspicions of the gate is that President Park imposed pressure on chaebols to make donations to the Mir Foundation, dominated by Choi Sun-sil, an aide to President Park Geun-hye. The Mir Foundation was established to spread the Korean Wave. How did the Korean Wave become the targets of abuse of power?

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      Mentions: Japan China IPO
    3. WKS401 Deploy a Deep Learning Framework on Amazon ECS and EC2 Spot Instances

      WKS401 Deploy a Deep Learning Framework on Amazon ECS and EC2 Spot Instances

      Deep learning is an implementation of machine learning that uses neural networks to solve difficult and complex problems, such as computer vision, natural language processing, and recommendations. Due to the availability of deep learning libraries and frameworks, developers have the ability to enhance the capabilities of their applications and projects. In this workshop, you learn how to build and deploy a powerful deep learning framework called MXNet on containers.

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      Mentions: AWS
    4. Spotify Discover Weekly: The machine learning behind your music recommendations

      Spotify Discover Weekly: The machine learning behind your music recommendations

      Published on Jul 1, 2017 In this presentation, I give an overview of the machine learning algorithms behind Spotify’s extraordinarily popular Discover Weekly playlist. I provide a brief introduction to what the playlist is, explain how music recommendation engines have evolved over time, then break down the three main algorithm types powering Spotify’s recommendations: (1) collaborative filtering, (2) Natural Language Processing (NLP), and (3) Raw audio analysis.

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      Mentions: Spotify
    5. Theory behind Image Compression and Semantic Search

      Theory behind Image Compression and Semantic Search

      Show related SlideShares at end WordPress Shortcode Theory behind Image Compression and Semantic Search 93 views Published on Jun 27, 2017 Singular Value Decomposition (SVD) is a matrix decomposition technique developed during the 18th century and has been in use ever since. SVD has applications in several areas including image processing, natural language processing (NLP), genomics, and data compression.

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    6. There's Something About Alexa: Is Retail Ready for the Age of Conversational Commerce?

      There's Something About Alexa: Is Retail Ready for the Age of Conversational Commerce?

      Amazon is investing billions into voice technology: Echo devices, Alexa skills, Natural Language Processing, and of course, shopping via Alexa. In this informative and educational presentation, targeted to retailers, Aptos Marketing Director Dave Bruno will walk you through the state of adoption of Echos and Alexa, Amazon;s Alexa strategy, how consumers are (or aren't shopping with Alexa, chat bots, and why he is worried most about something that has - on the surface, at least - nothing at all to do with shopping. ...

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      Mentions: Amazon
    7. Frame-based Sentiment Analysis with Sentilo

      Frame-based Sentiment Analysis with Sentilo

      Frame-based Sentiment Analysis with Sentilo 10 views Sentilo is an unsupervised, domain-independent system that performs sentiment analysis by hybridising natural language processing techniques and semantic Web technologies. Given a sentence expressing an opinion, Sentilo recognises its holder, detects the topics and subtopics that it targets, links them to relevant situations and events referred by it and evaluates the sentiment expressed on each topic/subtopic.

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      Mentions: RDF
    8. Getting Started with Natural Language Processing with Jason Anderson

      Getting Started with Natural Language Processing with Jason Anderson

      Getting Started with Natural Language Processing with Jason Anderson 36 views Published on May 27, 2017 With the advent of bot frameworks and voice-only devices, we are seeing a change with how humans interact with computers. Instead of humans learning computer interfaces—which can be largely non-intuitive—computers are instead learning how humans innately communicate with language. Powering this change is the field of Natural Language Processing (NLP).

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      Mentions: NLP
    9. bBridge

      bBridge

      Published on Feb 20, 2017 bBridge is a Big Data analytics platform that aims to bridge the gap between social media users, business and big data. It results in two closely related applications: bBridge Online, a social media analytics web portal and bBridge API, a social multimedia analytics API for other companies. bBridge Online offers real-time group analytics to business and public sector users.

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      Mentions: Big Data
    10. Automatic Error Detection and Correction in Malayalam

      Automatic Error Detection and Correction in Malayalam

      Show related SlideShares at end WordPress Shortcode Automatic Error Detection and Correction in Malayalam 4 views Published on Jan 4, 2017 Spelling error correction is a Natural Language Processing (NLP) problem, and it has recently become relevant because many of the potential NLP applications such as text summarization, sentiment analysis and machine translation etc take advantage of spelling error analysis. Spell checking is a well-known task in NLP.

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      Mentions: NLP Malayalam
    11. Using Natural Language Processing on large Github data

      Using Natural Language Processing on large Github data

      Show related SlideShares at end WordPress Shortcode Using Natural Language Processing on large Github data 5 views The aim of the project is to use existing data in large well developed GitHub repositories to build a knowledge base that can assist in the continued development of the project and in more quickly resolving issues posted to the repository. We are trying to tackle the current problem of manual curation.

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    12. Introduction to Natural Language Processing

      Introduction to Natural Language Processing

      Show related SlideShares at end WordPress Shortcode Introduction to Natural Language Processing 10 views Published on Nov 27, 2016 Undestanding unstructured text and extracting information from it is an active area of research. It is easy for a human to read a document, identify the keyphrases and get the gist of topic. Natural language has so many variations and intricacies that makes it challenging to design computing systems that can do intelligent processing.

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      Mentions: NLP
    13. A general method applicable to the search for anglicisms in russian social network texts

      A general method applicable to the search for anglicisms in russian social network texts

      Published on Nov 14, 2016 In the process of globalization, the number of English words in other languages has rapidly increased. In automatic speech recognition systems, spell-checking, tagging, and other software in the field of natural language processing, loan words are not easily recognized and should be evaluated separately. In this paper we present a corpora-based approach to the automatic detection of anglicisms in Russian social network texts.

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      Mentions: Russian
    14. Topic 4: The Magician's Hat: Turning Data into Business Intelligence

      Topic 4: The Magician's Hat: Turning Data into Business Intelligence

      Show related SlideShares at end WordPress Shortcode Topic 4: The Magician's Hat: Turning Data into Business Intelligence 1 view Yoshiyasu Yamakawa (Intel), JP Barraza (Systran), Konstantin Dranch (Memsource), David Koot (TAUS) The focus of this session will be on predictions and risk management. What kind of things can you predict and how can you manage risks by by analyzing your translation data or monitoring your productivity and quality.

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    15. SystemT: Declarative Information Extraction (invited talk at Mit Csail)

      SystemT: Declarative Information Extraction (invited talk at Mit Csail)

      Oct 7, 2016 Invited talk at MIT CSAIL, March 8 2016 Information extraction (IE), the task of extracting structured information from unstructured or semi-structured data, is increasingly important to a wide array of enterprise applications, ranging from Business Intelligence to Data-as-a-Service. Such applications drive the following main requirements for IE systems: accuracy, scalability, expressivity, transparency, and customizability.

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    16. Global Natural Language Processing NLP Market 2016

      Global Natural Language Processing NLP Market 2016

      Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy . Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.

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      Mentions: Japan China Germany
    17. An Application for Performing Real Time Speech Translation in Mobile Environment

      An Application for Performing Real Time Speech Translation in Mobile Environment

      Published on Jun 20, 2016 This paper presents the method of applying speaker-independent and bidirectional speech-to-speech translation system for spontaneous dialogs in real time calling system. This technique recognizes spoken input, analyzes and translates it, and finally utters the translation. The major part of Speech translation comes under Natural language processing.

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    18. Machine Translation Introduction

      Machine Translation Introduction

      Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy . Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.

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    19. Challenges in understanding clinical notes: Why NLP engines fall short and where background knowledge can help.

      Challenges in understanding clinical notes: Why NLP engines fall short and where background knowledge can help.

      Published on Jun 1, 2016 Understanding of Electronic Medical Records(EMRs) plays a crucial role in improving healthcare outcomes. However, the unstructured nature of EMRs poses several technical challenges for structured information extraction from clinical notes leading to automatic analysis.

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    1-22 of 22
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD