Machine Learning & AI

Size: px
Start display at page:

Download "Machine Learning & AI"

Transcription

1 Machine Learning & AI

2 Programs Offerings S.No Program 1. P.G. Diploma in Machine Learning and AI 2. Certification in Machine Learning & NLP 3. Certification in Machine Learning & Deep Learning 4. Certification in Machine Learning 5. Certification in NLP 6. Certification in Deep Learning [2018]. UpGrad Education Pvt. Ltd. All Rights Reserved.

3 PG Diploma in Machine Learning & AI [11 Months] The potential to recognize and use data insights to strategize services and solutions is critical in this data-centric world. Organizations today are adopting deep learning to analyze documents and images connected to a large database, identify speech or gestures, translate voice in real time, predictions with past information, and more. UpGrad s Machine Learning & AI program helps build essential Machine Learning skills that then progress to Deep Learning and AI specializations. Solutions consultants, Business analysts, Marketing professionals Statistics Essentials Machine Learning Natural Language Processing Neural Networks & Deep Learning Graphical Models Reinforcement Learning Use cutting edge AI techniques to teach a computer to play a computer game such as Tetris. Create and deploy complex neural networks to detect the occurrence of certain objects in images collected from various sources. Create a recommender system for users of a news app to aggregate news from various sources and provide personalised reading recommendations. Train a chatbot to classify sentences (customer queries etc.) into categories and respond to them. And many more

4 Cert. in Machine Learning & NLP [6 Months] Natural Language Processing (NLP) has found many business applications in areas of customer service, market intelligence, and regulatory compliance to name a few. But hiring specialized NLP skills is generally not a viable option for most organizations. UpGrad s program in Machine Learning & NLP helps progress the journey of a Machine Learning specialist to an NLP specialist. Professionals with Data Analysis and Programming background & Outcomes Machine Learning Linear Regression Logistic Regression Naïve Bayes Theorem Model Selection Support Vector Machines Tree Models Unsupervised Learning Clustering Advanced Regression NLP Lexical Processing Grammar and Document Models Semantic Processing Telecom Chum Case Study: Predict customers which are more likely to churn to competition using Predictive Analytics. HR Analytics Case Study: Use analytics to predict which employee is going to leave a company in the near future. Chatbot Engine: Training a Chatbot Engine to understand and respond to customer requests for flight reservations News Recommender Engine: Create a news recommender engine which classifies news articles and provides personalized reading recommendations

5 Cert. in Machine Learning & Deep Learning [6 Months] The potential to recognize and use data insights to strategize services and solutions is critical in this data-centric world. Organizations today are adopting deep learning to analyze documents and images connected to a large database, identify speech or gestures, translate voice in real time, predictions with past information, and more. UpGrad s Machine Learning & Deep Learning program helps progress the journey of a Machine Learning specialist to an Deep Learning specialist. Professionals with Data Analysis and Programming background Machine Learning Linear Regression Logistic Regression Naïve Bayes Theorem Model Selection Support Vector Machines Tree Models Unsupervised learning Clustering Advanced Regression Deep Learning Information flow in a Neural Network Training a Neural Network - Assignment Convolutional Neural Networks Recurrent Neural Networks Telecom Chum Case Study: Predict customers which are more likely to churn to competition using Predictive Analytics. HR Analytics Case Study: Use analytics to predict which employee is going to leave a company in the near future. Object Detection in Images: Diagnose illnesses using deep neural networks build on medical images such as MRI, X-Rays, CT Scan, etc And many more

6 Certification in Machine Learning [3 months] Recruiting Machine Learning specialists is a challenge for organizations as the domain is till very young; since most projects in machine learning are still exploratory and/or experimental in nature, it makes it further challenging for organizations to narrow down to skills and qualities that are particularly valuable for their business background in data analysis. UpGrad s entry level program in Machine Learning is a segway for data analysts to move into senior data scientist roles and at the same time creates parallel career pathways in the field of Machine Learning Data Science Professionals who have completed the Data Analyst course or have equivalent relevant experience Linear Regression Logistic Regression Naïve Bayes Theorem Model Selection Support Vector Machines Tree Models Unsupervised learning Clustering Advanced Regression Telecom Chum Case Study- Predict customers which are more likely to churn to competition using Predictive Analytics. HR Analytics Case Study- Use analytics to predict which employee is going to leave a company in the near future.

7 Certification in NLP [3 months] Natural Language Processing (NLP) has found many business applications in areas of customer service, market intelligence, and regulatory compliance to name a few. But hiring specialized NLP skills is generally not a viable option for most organizations. UpGrad s program in NLP helps progress the journey of a Machine Learning specialist to an NLP specialist Data Science Professionals who have completed the Machine Learning Specialist course or have equivalent relevant experience Lexical Processing Grammar and Document Models Semantic Processing Chatbot Engine: Training a Chatbot Engine to understand and respond to customer requests for flight reservations News Recommender Engine: Create a news recommender engine which classifies news articles and provides personalized reading recommendations

8 Certification in Deep Learning [3 months] The potential to recognize and use data insights to strategize services and solutions is critical in this data-centric world. Organizations today are adopting deep learning to analyze documents and images connected to a large database, identify speech or gestures, translate voice in real time, predictions with past information, and more. UpGrad s Deep Learning program helps progress the journey of a Machine Learning specialist to an Deep Learning specialist. Data Science Professionals who have completed the Machine Learning Specialist course or have equivalent relevant experience Information flow in a Neural Network [20 hours] Training a Neural Network - Assignment [10 hours] Convolutional Neural Networks [20 hours] Recurrent Neural Networks [10 hours] Object Detection in Images: Diagnose illnesses using deep neural networks build on medical images such as MRI, X-Rays, CT Scan, etc And many more

9 Thank You

Python Machine Learning

Python Machine Learning Python Machine Learning Unlock deeper insights into machine learning with this vital guide to cuttingedge predictive analytics Sebastian Raschka [ PUBLISHING 1 open source I community experience distilled

More information

Module 12. Machine Learning. Version 2 CSE IIT, Kharagpur

Module 12. Machine Learning. Version 2 CSE IIT, Kharagpur Module 12 Machine Learning 12.1 Instructional Objective The students should understand the concept of learning systems Students should learn about different aspects of a learning system Students should

More information

Business Analytics and Information Tech COURSE NUMBER: 33:136:494 COURSE TITLE: Data Mining and Business Intelligence

Business Analytics and Information Tech COURSE NUMBER: 33:136:494 COURSE TITLE: Data Mining and Business Intelligence Business Analytics and Information Tech COURSE NUMBER: 33:136:494 COURSE TITLE: Data Mining and Business Intelligence COURSE DESCRIPTION This course presents computing tools and concepts for all stages

More information

The 9 th International Scientific Conference elearning and software for Education Bucharest, April 25-26, / X

The 9 th International Scientific Conference elearning and software for Education Bucharest, April 25-26, / X The 9 th International Scientific Conference elearning and software for Education Bucharest, April 25-26, 2013 10.12753/2066-026X-13-154 DATA MINING SOLUTIONS FOR DETERMINING STUDENT'S PROFILE Adela BÂRA,

More information

Top US Tech Talent for the Top China Tech Company

Top US Tech Talent for the Top China Tech Company THE FALL 2017 US RECRUITING TOUR Top US Tech Talent for the Top China Tech Company INTERVIEWS IN 7 CITIES Tour Schedule CITY Boston, MA New York, NY Pittsburgh, PA Urbana-Champaign, IL Ann Arbor, MI Los

More information

OFFICE SUPPORT SPECIALIST Technical Diploma

OFFICE SUPPORT SPECIALIST Technical Diploma OFFICE SUPPORT SPECIALIST Technical Diploma Program Code: 31-106-8 our graduates INDEMAND 2017/2018 mstc.edu administrative professional career pathway OFFICE SUPPORT SPECIALIST CUSTOMER RELATIONSHIP PROFESSIONAL

More information

Lecture 1: Machine Learning Basics

Lecture 1: Machine Learning Basics 1/69 Lecture 1: Machine Learning Basics Ali Harakeh University of Waterloo WAVE Lab ali.harakeh@uwaterloo.ca May 1, 2017 2/69 Overview 1 Learning Algorithms 2 Capacity, Overfitting, and Underfitting 3

More information

Lecture 1: Basic Concepts of Machine Learning

Lecture 1: Basic Concepts of Machine Learning Lecture 1: Basic Concepts of Machine Learning Cognitive Systems - Machine Learning Ute Schmid (lecture) Johannes Rabold (practice) Based on slides prepared March 2005 by Maximilian Röglinger, updated 2010

More information

ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY DOWNLOAD EBOOK : ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY PDF

ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY DOWNLOAD EBOOK : ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY PDF Read Online and Download Ebook ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY DOWNLOAD EBOOK : ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY PDF Click link bellow and free register to download

More information

MASTER OF SCIENCE (M.S.) MAJOR IN COMPUTER SCIENCE

MASTER OF SCIENCE (M.S.) MAJOR IN COMPUTER SCIENCE Master of Science (M.S.) Major in Computer Science 1 MASTER OF SCIENCE (M.S.) MAJOR IN COMPUTER SCIENCE Major Program The programs in computer science are designed to prepare students for doctoral research,

More information

Programme Specification

Programme Specification Programme Specification Title: Accounting and Finance Final Award: Master of Science (MSc) With Exit Awards at: Postgraduate Certificate (PG Cert) Postgraduate Diploma (PG Dip) Master of Science (MSc)

More information

Deep search. Enhancing a search bar using machine learning. Ilgün Ilgün & Cedric Reichenbach

Deep search. Enhancing a search bar using machine learning. Ilgün Ilgün & Cedric Reichenbach #BaselOne7 Deep search Enhancing a search bar using machine learning Ilgün Ilgün & Cedric Reichenbach We are not researchers Outline I. Periscope: A search tool II. Goals III. Deep learning IV. Applying

More information

Programme Specification

Programme Specification Programme Specification Title: Crisis and Disaster Management Final Award: Master of Science (MSc) With Exit Awards at: Postgraduate Certificate (PG Cert) Postgraduate Diploma (PG Dip) Master of Science

More information

(Sub)Gradient Descent

(Sub)Gradient Descent (Sub)Gradient Descent CMSC 422 MARINE CARPUAT marine@cs.umd.edu Figures credit: Piyush Rai Logistics Midterm is on Thursday 3/24 during class time closed book/internet/etc, one page of notes. will include

More information

Courses in English. Application Development Technology. Artificial Intelligence. 2017/18 Spring Semester. Database access

Courses in English. Application Development Technology. Artificial Intelligence. 2017/18 Spring Semester. Database access The courses availability depends on the minimum number of registered students (5). If the course couldn t start, students can still complete it in the form of project work and regular consultations with

More information

Unit 7 Data analysis and design

Unit 7 Data analysis and design 2016 Suite Cambridge TECHNICALS LEVEL 3 IT Unit 7 Data analysis and design A/507/5007 Guided learning hours: 60 Version 2 - revised May 2016 *changes indicated by black vertical line ocr.org.uk/it LEVEL

More information

Twitter Sentiment Classification on Sanders Data using Hybrid Approach

Twitter Sentiment Classification on Sanders Data using Hybrid Approach IOSR Journal of Computer Engineering (IOSR-JCE) e-issn: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 4, Ver. I (July Aug. 2015), PP 118-123 www.iosrjournals.org Twitter Sentiment Classification on Sanders

More information

English Language and Applied Linguistics. Module Descriptions 2017/18

English Language and Applied Linguistics. Module Descriptions 2017/18 English Language and Applied Linguistics Module Descriptions 2017/18 Level I (i.e. 2 nd Yr.) Modules Please be aware that all modules are subject to availability. If you have any questions about the modules,

More information

CSL465/603 - Machine Learning

CSL465/603 - Machine Learning CSL465/603 - Machine Learning Fall 2016 Narayanan C Krishnan ckn@iitrpr.ac.in Introduction CSL465/603 - Machine Learning 1 Administrative Trivia Course Structure 3-0-2 Lecture Timings Monday 9.55-10.45am

More information

Natural Language Processing. George Konidaris

Natural Language Processing. George Konidaris Natural Language Processing George Konidaris gdk@cs.brown.edu Fall 2017 Natural Language Processing Understanding spoken/written sentences in a natural language. Major area of research in AI. Why? Humans

More information

A Decision Tree Analysis of the Transfer Student Emma Gunu, MS Research Analyst Robert M Roe, PhD Executive Director of Institutional Research and

A Decision Tree Analysis of the Transfer Student Emma Gunu, MS Research Analyst Robert M Roe, PhD Executive Director of Institutional Research and A Decision Tree Analysis of the Transfer Student Emma Gunu, MS Research Analyst Robert M Roe, PhD Executive Director of Institutional Research and Planning Overview Motivation for Analyses Analyses and

More information

A Case Study: News Classification Based on Term Frequency

A Case Study: News Classification Based on Term Frequency A Case Study: News Classification Based on Term Frequency Petr Kroha Faculty of Computer Science University of Technology 09107 Chemnitz Germany kroha@informatik.tu-chemnitz.de Ricardo Baeza-Yates Center

More information

Mining Association Rules in Student s Assessment Data

Mining Association Rules in Student s Assessment Data www.ijcsi.org 211 Mining Association Rules in Student s Assessment Data Dr. Varun Kumar 1, Anupama Chadha 2 1 Department of Computer Science and Engineering, MVN University Palwal, Haryana, India 2 Anupama

More information

Nearing Completion of Prototype 1: Discovery

Nearing Completion of Prototype 1: Discovery The Fit-Gap Report The Fit-Gap Report documents how where the PeopleSoft software fits our needs and where LACCD needs to change functionality or business processes to reach the desired outcome. The report

More information

Generative models and adversarial training

Generative models and adversarial training Day 4 Lecture 1 Generative models and adversarial training Kevin McGuinness kevin.mcguinness@dcu.ie Research Fellow Insight Centre for Data Analytics Dublin City University What is a generative model?

More information

Applications of data mining algorithms to analysis of medical data

Applications of data mining algorithms to analysis of medical data Master Thesis Software Engineering Thesis no: MSE-2007:20 August 2007 Applications of data mining algorithms to analysis of medical data Dariusz Matyja School of Engineering Blekinge Institute of Technology

More information

Text-mining the Estonian National Electronic Health Record

Text-mining the Estonian National Electronic Health Record Text-mining the Estonian National Electronic Health Record Raul Sirel rsirel@ut.ee 13.11.2015 Outline Electronic Health Records & Text Mining De-identifying the Texts Resolving the Abbreviations Terminology

More information

USER ADAPTATION IN E-LEARNING ENVIRONMENTS

USER ADAPTATION IN E-LEARNING ENVIRONMENTS USER ADAPTATION IN E-LEARNING ENVIRONMENTS Paraskevi Tzouveli Image, Video and Multimedia Systems Laboratory School of Electrical and Computer Engineering National Technical University of Athens tpar@image.

More information

DOUBLE DEGREE PROGRAM AT EURECOM. June 2017 Caroline HANRAS International Relations Manager

DOUBLE DEGREE PROGRAM AT EURECOM. June 2017 Caroline HANRAS International Relations Manager DOUBLE DEGREE PROGRAM AT EURECOM June 2017 Caroline HANRAS International Relations Manager KEY FACTS 1991 Creation by EPFL and Telecom ParisTech 3 Main Fields of Expertise 300 23 Master Students Professors

More information

Learning Methods for Fuzzy Systems

Learning Methods for Fuzzy Systems Learning Methods for Fuzzy Systems Rudolf Kruse and Andreas Nürnberger Department of Computer Science, University of Magdeburg Universitätsplatz, D-396 Magdeburg, Germany Phone : +49.39.67.876, Fax : +49.39.67.8

More information

Operational Knowledge Management: a way to manage competence

Operational Knowledge Management: a way to manage competence Operational Knowledge Management: a way to manage competence Giulio Valente Dipartimento di Informatica Universita di Torino Torino (ITALY) e-mail: valenteg@di.unito.it Alessandro Rigallo Telecom Italia

More information

Probabilistic Latent Semantic Analysis

Probabilistic Latent Semantic Analysis Probabilistic Latent Semantic Analysis Thomas Hofmann Presentation by Ioannis Pavlopoulos & Andreas Damianou for the course of Data Mining & Exploration 1 Outline Latent Semantic Analysis o Need o Overview

More information

We are strong in research and particularly noted in software engineering, information security and privacy, and humane gaming.

We are strong in research and particularly noted in software engineering, information security and privacy, and humane gaming. Computer Science 1 COMPUTER SCIENCE Office: Department of Computer Science, ECS, Suite 379 Mail Code: 2155 E Wesley Avenue, Denver, CO 80208 Phone: 303-871-2458 Email: info@cs.du.edu Web Site: Computer

More information

UNIVERSITY OF NORTH GEORGIA ADMINISTRATIVE / PROFESSIONAL PAY PLAN FISCAL YEAR 2015 BENEFITS-ELIGIBLE EXEMPT (MONTHLY) EMPLOYEES

UNIVERSITY OF NORTH GEORGIA ADMINISTRATIVE / PROFESSIONAL PAY PLAN FISCAL YEAR 2015 BENEFITS-ELIGIBLE EXEMPT (MONTHLY) EMPLOYEES -A- Academic Advisor 533925 16 EX 3 410X Academic Counselor 533928 16 EX 3 410X Academic Affairs Administrative Liaison 533913 18 EX 3 325X Academic Affairs Business Manager 533912 20 EX 3 325X Academic

More information

System Implementation for SemEval-2017 Task 4 Subtask A Based on Interpolated Deep Neural Networks

System Implementation for SemEval-2017 Task 4 Subtask A Based on Interpolated Deep Neural Networks System Implementation for SemEval-2017 Task 4 Subtask A Based on Interpolated Deep Neural Networks 1 Tzu-Hsuan Yang, 2 Tzu-Hsuan Tseng, and 3 Chia-Ping Chen Department of Computer Science and Engineering

More information

Linking Task: Identifying authors and book titles in verbose queries

Linking Task: Identifying authors and book titles in verbose queries Linking Task: Identifying authors and book titles in verbose queries Anaïs Ollagnier, Sébastien Fournier, and Patrice Bellot Aix-Marseille University, CNRS, ENSAM, University of Toulon, LSIS UMR 7296,

More information

Australian Journal of Basic and Applied Sciences

Australian Journal of Basic and Applied Sciences AENSI Journals Australian Journal of Basic and Applied Sciences ISSN:1991-8178 Journal home page: www.ajbasweb.com Feature Selection Technique Using Principal Component Analysis For Improving Fuzzy C-Mean

More information

CS4491/CS 7265 BIG DATA ANALYTICS INTRODUCTION TO THE COURSE. Mingon Kang, PhD Computer Science, Kennesaw State University

CS4491/CS 7265 BIG DATA ANALYTICS INTRODUCTION TO THE COURSE. Mingon Kang, PhD Computer Science, Kennesaw State University CS4491/CS 7265 BIG DATA ANALYTICS INTRODUCTION TO THE COURSE Mingon Kang, PhD Computer Science, Kennesaw State University Self Introduction Mingon Kang, PhD Homepage: http://ksuweb.kennesaw.edu/~mkang9

More information

Training a Neural Network to Answer 8th Grade Science Questions Steven Hewitt, An Ju, Katherine Stasaski

Training a Neural Network to Answer 8th Grade Science Questions Steven Hewitt, An Ju, Katherine Stasaski Training a Neural Network to Answer 8th Grade Science Questions Steven Hewitt, An Ju, Katherine Stasaski Problem Statement and Background Given a collection of 8th grade science questions, possible answer

More information

2017 FALL PROFESSIONAL TRAINING CALENDAR

2017 FALL PROFESSIONAL TRAINING CALENDAR 2017 FALL PROFESSIONAL TRAINING CALENDAR Date Title Price Instructor Sept 20, 1:30 4:30pm Feedback to boost employee performance 50 Euros Sept 26, 1:30 4:30pm Dealing with Customer Objections 50 Euros

More information

Welcome to. ECML/PKDD 2004 Community meeting

Welcome to. ECML/PKDD 2004 Community meeting Welcome to ECML/PKDD 2004 Community meeting A brief report from the program chairs Jean-Francois Boulicaut, INSA-Lyon, France Floriana Esposito, University of Bari, Italy Fosca Giannotti, ISTI-CNR, Pisa,

More information

Learning Structural Correspondences Across Different Linguistic Domains with Synchronous Neural Language Models

Learning Structural Correspondences Across Different Linguistic Domains with Synchronous Neural Language Models Learning Structural Correspondences Across Different Linguistic Domains with Synchronous Neural Language Models Stephan Gouws and GJ van Rooyen MIH Medialab, Stellenbosch University SOUTH AFRICA {stephan,gvrooyen}@ml.sun.ac.za

More information

Speech Recognition at ICSI: Broadcast News and beyond

Speech Recognition at ICSI: Broadcast News and beyond Speech Recognition at ICSI: Broadcast News and beyond Dan Ellis International Computer Science Institute, Berkeley CA Outline 1 2 3 The DARPA Broadcast News task Aspects of ICSI

More information

University of the Arts London (UAL) Diploma in Professional Studies Art and Design Date of production/revision May 2015

University of the Arts London (UAL) Diploma in Professional Studies Art and Design Date of production/revision May 2015 Programme Specification Every taught course of study leading to a UAL award is required to have a Programme Specification. This summarises the course aims, learning outcomes, teaching, learning and assessment

More information

21 st Century Apprenticeship Models

21 st Century Apprenticeship Models 21 st Century Apprenticeship Models Marjorie Valentin, Three Rivers Community College Donna Lawrence, Midlands Technical College Eric Roe, PhD, Polk State College Linda Head, Lone Star College System Let

More information

A Bayesian Learning Approach to Concept-Based Document Classification

A Bayesian Learning Approach to Concept-Based Document Classification Databases and Information Systems Group (AG5) Max-Planck-Institute for Computer Science Saarbrücken, Germany A Bayesian Learning Approach to Concept-Based Document Classification by Georgiana Ifrim Supervisors

More information

Universidade do Minho Escola de Engenharia

Universidade do Minho Escola de Engenharia Universidade do Minho Escola de Engenharia Universidade do Minho Escola de Engenharia Dissertação de Mestrado Knowledge Discovery is the nontrivial extraction of implicit, previously unknown, and potentially

More information

Rule Learning With Negation: Issues Regarding Effectiveness

Rule Learning With Negation: Issues Regarding Effectiveness Rule Learning With Negation: Issues Regarding Effectiveness S. Chua, F. Coenen, G. Malcolm University of Liverpool Department of Computer Science, Ashton Building, Ashton Street, L69 3BX Liverpool, United

More information

Learning From the Past with Experiment Databases

Learning From the Past with Experiment Databases Learning From the Past with Experiment Databases Joaquin Vanschoren 1, Bernhard Pfahringer 2, and Geoff Holmes 2 1 Computer Science Dept., K.U.Leuven, Leuven, Belgium 2 Computer Science Dept., University

More information

Reducing Features to Improve Bug Prediction

Reducing Features to Improve Bug Prediction Reducing Features to Improve Bug Prediction Shivkumar Shivaji, E. James Whitehead, Jr., Ram Akella University of California Santa Cruz {shiv,ejw,ram}@soe.ucsc.edu Sunghun Kim Hong Kong University of Science

More information

Indian Institute of Technology, Kanpur

Indian Institute of Technology, Kanpur Indian Institute of Technology, Kanpur Course Project - CS671A POS Tagging of Code Mixed Text Ayushman Sisodiya (12188) {ayushmn@iitk.ac.in} Donthu Vamsi Krishna (15111016) {vamsi@iitk.ac.in} Sandeep Kumar

More information

Axiom 2013 Team Description Paper

Axiom 2013 Team Description Paper Axiom 2013 Team Description Paper Mohammad Ghazanfari, S Omid Shirkhorshidi, Farbod Samsamipour, Hossein Rahmatizadeh Zagheli, Mohammad Mahdavi, Payam Mohajeri, S Abbas Alamolhoda Robotics Scientific Association

More information

Network Technology/Cisco and Linux Networking Education Report. 5, % $27.63/hr

Network Technology/Cisco and Linux Networking Education Report. 5, % $27.63/hr Network Technology/Cisco and Linux Networking Education Report CIP 11.91 Cochise, Pima, SC CIP 21: A program that focuses on the design, implementation, and management of linked systems of computers, peripherals,

More information

Trend Survey on Japanese Natural Language Processing Studies over the Last Decade

Trend Survey on Japanese Natural Language Processing Studies over the Last Decade Trend Survey on Japanese Natural Language Processing Studies over the Last Decade Masaki Murata, Koji Ichii, Qing Ma,, Tamotsu Shirado, Toshiyuki Kanamaru,, and Hitoshi Isahara National Institute of Information

More information

Laboratorio di Intelligenza Artificiale e Robotica

Laboratorio di Intelligenza Artificiale e Robotica Laboratorio di Intelligenza Artificiale e Robotica A.A. 2008-2009 Outline 2 Machine Learning Unsupervised Learning Supervised Learning Reinforcement Learning Genetic Algorithms Genetics-Based Machine Learning

More information

A Comparison of Two Text Representations for Sentiment Analysis

A Comparison of Two Text Representations for Sentiment Analysis 010 International Conference on Computer Application and System Modeling (ICCASM 010) A Comparison of Two Text Representations for Sentiment Analysis Jianxiong Wang School of Computer Science & Educational

More information

Short Text Understanding Through Lexical-Semantic Analysis

Short Text Understanding Through Lexical-Semantic Analysis Short Text Understanding Through Lexical-Semantic Analysis Wen Hua #1, Zhongyuan Wang 2, Haixun Wang 3, Kai Zheng #4, Xiaofang Zhou #5 School of Information, Renmin University of China, Beijing, China

More information

Multi-tasks Deep Learning Model for classifying MRI images of AD/MCI Patients

Multi-tasks Deep Learning Model for classifying MRI images of AD/MCI Patients Multi-tasks Deep Learning Model for classifying MRI images of AD/MCI Patients S.Sambath Kumar 1, Dr M. Nandhini 2, 1 Research scholar, 2 Assistant Professor 1,2 Department of Computer Science, Pondicherry

More information

Closing out the School Year for Teachers and Administrators Spring PANC Conference Wrightsville Beach April 7-9, 2014

Closing out the School Year for Teachers and Administrators Spring PANC Conference Wrightsville Beach April 7-9, 2014 Closing out the School Year for Teachers and Administrators 2014 Spring PANC Conference Wrightsville Beach April 7-9, 2014 Presenter Tad Piner IIS Functional System Analyst 919.807.3223 Learning Outcomes

More information

Citrine Informatics. The Latest from Citrine. Citrine Informatics. The data analytics platform for the physical world

Citrine Informatics. The Latest from Citrine. Citrine Informatics. The data analytics platform for the physical world Citrine Informatics The data analytics platform for the physical world The Latest from Citrine Summit on Data and Analytics for Materials Research 31 October 2016 Our Mission is Simple Add as much value

More information

Programme Specification

Programme Specification Programme Specification Title: Journalism (War and International Human Rights) Final Award: Master of Arts (MA) With Exit Awards at: Postgraduate Certificate (PG Cert) Postgraduate Diploma (PG Dip) Master

More information

STA 225: Introductory Statistics (CT)

STA 225: Introductory Statistics (CT) Marshall University College of Science Mathematics Department STA 225: Introductory Statistics (CT) Course catalog description A critical thinking course in applied statistical reasoning covering basic

More information

Welcome. Paulo Goes Dean, Eller College of Management Welcome Our region

Welcome. Paulo Goes Dean, Eller College of Management Welcome Our region Welcome. Paulo Goes Dean, Welcome. Our region Outlook for Tucson Patricia Feeney Executive Director, Southern Arizona Market Chase George W. Hammond, Ph.D. Director, University of Arizona 1 Visit the award-winning

More information

Unsupervised Learning of Word Semantic Embedding using the Deep Structured Semantic Model

Unsupervised Learning of Word Semantic Embedding using the Deep Structured Semantic Model Unsupervised Learning of Word Semantic Embedding using the Deep Structured Semantic Model Xinying Song, Xiaodong He, Jianfeng Gao, Li Deng Microsoft Research, One Microsoft Way, Redmond, WA 98052, U.S.A.

More information

Tulsa Community College Staff Salary Schedule (Effective July 1, 2015)

Tulsa Community College Staff Salary Schedule (Effective July 1, 2015) Grade 4 Minimum $16,377 Midpoint $20,062 Maximum $23,747 Grade 5 Minimum $17,761 Midpoint $21,868 Maximum $25,975 Grade 6 Minimum $19,309 Midpoint $23,895 Maximum $28,481 Grade 7 Minimum $21,044 Midpoint

More information

ON BEHAVIORAL PROCESS MODEL SIMILARITY MATCHING A CENTROID-BASED APPROACH

ON BEHAVIORAL PROCESS MODEL SIMILARITY MATCHING A CENTROID-BASED APPROACH MICHAELA BAUMANN, M.SC. ON BEHAVIORAL PROCESS MODEL SIMILARITY MATCHING A CENTROID-BASED APPROACH MICHAELA BAUMANN, MICHAEL HEINRICH BAUMANN, STEFAN JABLONSKI THE TENTH INTERNATIONAL MULTI-CONFERENCE ON

More information

IMPROVE THE QUALITY OF WELDING

IMPROVE THE QUALITY OF WELDING Virtual Welding Simulator PATENT PENDING Application No. 1020/CHE/2013 AT FIRST GLANCE The Virtual Welding Simulator is an advanced technology based training and performance evaluation simulator. It simulates

More information

Enhancing Customer Service through Learning Technology

Enhancing Customer Service through Learning Technology C a s e S t u d y Enhancing Customer Service through Learning Technology John Hancock Implements an online learning solution which integrates training, performance support, and assessment Chris Howard

More information

Interactive Whiteboard

Interactive Whiteboard 50 Graphic Organizers for the Interactive Whiteboard Whiteboard-ready graphic organizers for reading, writing, math, and more to make learning engaging and interactive by Jennifer Jacobson & Dottie Raymer

More information

Dinesh K. Sharma, Ph.D. Department of Management School of Business and Economics Fayetteville State University

Dinesh K. Sharma, Ph.D. Department of Management School of Business and Economics Fayetteville State University Department of Management School of Business and Economics Fayetteville State University EDUCATION Doctor of Philosophy, Devi Ahilya University, Indore, India (2013) Area of Specialization: Management:

More information

What Can Neural Networks Teach us about Language? Graham Neubig a2-dlearn 11/18/2017

What Can Neural Networks Teach us about Language? Graham Neubig a2-dlearn 11/18/2017 What Can Neural Networks Teach us about Language? Graham Neubig a2-dlearn 11/18/2017 Supervised Training of Neural Networks for Language Training Data Training Model this is an example the cat went to

More information

Using Web Searches on Important Words to Create Background Sets for LSI Classification

Using Web Searches on Important Words to Create Background Sets for LSI Classification Using Web Searches on Important Words to Create Background Sets for LSI Classification Sarah Zelikovitz and Marina Kogan College of Staten Island of CUNY 2800 Victory Blvd Staten Island, NY 11314 Abstract

More information

Intuitive Practitioner Course Overview

Intuitive Practitioner Course Overview Intuitive Practitioner Course Overview About MetaVarsity The physical world that we perceive with our physical senses is the world of effects, the end result. What is the cause of this physical effect?

More information

Notes on The Sciences of the Artificial Adapted from a shorter document written for course (Deciding What to Design) 1

Notes on The Sciences of the Artificial Adapted from a shorter document written for course (Deciding What to Design) 1 Notes on The Sciences of the Artificial Adapted from a shorter document written for course 17-652 (Deciding What to Design) 1 Ali Almossawi December 29, 2005 1 Introduction The Sciences of the Artificial

More information

STABILISATION AND PROCESS IMPROVEMENT IN NAB

STABILISATION AND PROCESS IMPROVEMENT IN NAB STABILISATION AND PROCESS IMPROVEMENT IN NAB Authors: Nicole Warren Quality & Process Change Manager, Bachelor of Engineering (Hons) and Science Peter Atanasovski - Quality & Process Change Manager, Bachelor

More information

THE world surrounding us involves multiple modalities

THE world surrounding us involves multiple modalities 1 Multimodal Machine Learning: A Survey and Taxonomy Tadas Baltrušaitis, Chaitanya Ahuja, and Louis-Philippe Morency arxiv:1705.09406v2 [cs.lg] 1 Aug 2017 Abstract Our experience of the world is multimodal

More information

SERVICE-LEARNING Annual Report July 30, 2004 Kara Hartmann, Service-Learning Coordinator Page 1 of 5

SERVICE-LEARNING Annual Report July 30, 2004 Kara Hartmann, Service-Learning Coordinator Page 1 of 5 Page 1 of 5 PROFILE The mission of the Service-Learning Program is to foster citizenship and enhance learning through active involvement in academically-based community service. Service-Learning is a teaching

More information

Semi-supervised methods of text processing, and an application to medical concept extraction. Yacine Jernite Text-as-Data series September 17.

Semi-supervised methods of text processing, and an application to medical concept extraction. Yacine Jernite Text-as-Data series September 17. Semi-supervised methods of text processing, and an application to medical concept extraction Yacine Jernite Text-as-Data series September 17. 2015 What do we want from text? 1. Extract information 2. Link

More information

BEYOND THE BLEND. Getting Learning & Development Right. By Charles Jennings

BEYOND THE BLEND. Getting Learning & Development Right. By Charles Jennings BEYOND THE BLEND By Charles Jennings Brought to you by in association with 3 Foreword Technology has changed how we deliver learning and development (L&D), opening up new channels and possibilities for

More information

Statistics and Data Analytics Minor

Statistics and Data Analytics Minor October 28, 2014 Page 1 of 6 PROGRAM IDENTIFICATION NAME OF THE MINOR Statistics and Data Analytics ACADEMIC PROGRAM PROPOSING THE MINOR Mathematics PROGRAM DESCRIPTION DESCRIPTION OF THE MINOR AND STUDENT

More information

Platform for the Development of Accessible Vocational Training

Platform for the Development of Accessible Vocational Training Platform for the Development of Accessible Vocational Training Executive Summary January/2013 Acknowledgment Supported by: FINEP Contract 03.11.0371.00 SEL PUB MCT/FINEP/FNDCT/SUBV ECONOMICA A INOVACAO

More information

SRI LANKA INSTITUTE OF ADVANCED TECHNOLOGICAL EDUCATION REVISED CURRICULUM HIGHER NATIONAL DIPLOMA IN ENGLISH. September 2010

SRI LANKA INSTITUTE OF ADVANCED TECHNOLOGICAL EDUCATION REVISED CURRICULUM HIGHER NATIONAL DIPLOMA IN ENGLISH. September 2010 SRI LANKA INSTITUTE OF ADVANCED TECHNOLOGICAL EDUCATION REVISED CURRICULUM HIGHER NATIONAL DIPLOMA IN ENGLISH September 2010 Produced by MG Consultants (Pvt) Ltd, 267, Pannipitiya Road, Pelawatte, Battaramulla

More information

Lessons from a Massive Open Online Course (MOOC) on Natural Language Processing for Digital Humanities

Lessons from a Massive Open Online Course (MOOC) on Natural Language Processing for Digital Humanities Lessons from a Massive Open Online Course (MOOC) on Natural Language Processing for Digital Humanities Simon Clematide, Isabel Meraner, Noah Bubenhofer, Martin Volk Institute of Computational Linguistics

More information

Introduction to Ensemble Learning Featuring Successes in the Netflix Prize Competition

Introduction to Ensemble Learning Featuring Successes in the Netflix Prize Competition Introduction to Ensemble Learning Featuring Successes in the Netflix Prize Competition Todd Holloway Two Lecture Series for B551 November 20 & 27, 2007 Indiana University Outline Introduction Bias and

More information

1. Programme title and designation International Management N/A

1. Programme title and designation International Management N/A PROGRAMME APPROVAL FORM SECTION 1 THE PROGRAMME SPECIFICATION 1. Programme title and designation International Management 2. Final award Award Title Credit value ECTS Any special criteria equivalent MSc

More information

Human-Computer Interaction CS Overview for Today. Who am I? 1/15/2012. Prof. Stephen Intille

Human-Computer Interaction CS Overview for Today. Who am I? 1/15/2012. Prof. Stephen Intille Human-Computer Interaction CS 5340 Prof. Stephen Intille (Many thanks to Prof. Tim Bickmore) Overview for Today Introductions Overview of the Course First homework exercise Model Paper Presentations Logistics

More information

DNV GL Joint Industry Project: Decision Support for Dynamic Barrier Management

DNV GL Joint Industry Project: Decision Support for Dynamic Barrier Management DNV GL Joint Industry Project: Decision Support for Dynamic Barrier Management IADC/DEC Tech Forum Data Acquisition & Cybersecurity Bill Nelson 1 SAFER, SMARTER, GREENER DNV GL Joint Industry Project:

More information

Impact of Cluster Validity Measures on Performance of Hybrid Models Based on K-means and Decision Trees

Impact of Cluster Validity Measures on Performance of Hybrid Models Based on K-means and Decision Trees Impact of Cluster Validity Measures on Performance of Hybrid Models Based on K-means and Decision Trees Mariusz Łapczy ski 1 and Bartłomiej Jefma ski 2 1 The Chair of Market Analysis and Marketing Research,

More information

Word Segmentation of Off-line Handwritten Documents

Word Segmentation of Off-line Handwritten Documents Word Segmentation of Off-line Handwritten Documents Chen Huang and Sargur N. Srihari {chuang5, srihari}@cedar.buffalo.edu Center of Excellence for Document Analysis and Recognition (CEDAR), Department

More information

BYLINE [Heng Ji, Computer Science Department, New York University,

BYLINE [Heng Ji, Computer Science Department, New York University, INFORMATION EXTRACTION BYLINE [Heng Ji, Computer Science Department, New York University, hengji@cs.nyu.edu] SYNONYMS NONE DEFINITION Information Extraction (IE) is a task of extracting pre-specified types

More information

Higher Education Review (Embedded Colleges) of Navitas UK Holdings Ltd. Hertfordshire International College

Higher Education Review (Embedded Colleges) of Navitas UK Holdings Ltd. Hertfordshire International College Higher Education Review (Embedded Colleges) of Navitas UK Holdings Ltd April 2016 Contents About this review... 1 Key findings... 2 QAA's judgements about... 2 Good practice... 2 Theme: Digital Literacies...

More information

Integrating E-learning Environments with Computational Intelligence Assessment Agents

Integrating E-learning Environments with Computational Intelligence Assessment Agents Integrating E-learning Environments with Computational Intelligence Assessment Agents Christos E. Alexakos, Konstantinos C. Giotopoulos, Eleni J. Thermogianni, Grigorios N. Beligiannis and Spiridon D.

More information

Content-based Image Retrieval Using Image Regions as Query Examples

Content-based Image Retrieval Using Image Regions as Query Examples Content-based Image Retrieval Using Image Regions as Query Examples D. N. F. Awang Iskandar James A. Thom S. M. M. Tahaghoghi School of Computer Science and Information Technology, RMIT University Melbourne,

More information

Nottingham Trent University Course Specification

Nottingham Trent University Course Specification Nottingham Trent University Course Specification Basic Course Information 1. Awarding Institution: Nottingham Trent University 2. School/Campus: Nottingham Business School / City 3. Final Award, Course

More information

VOL VISION 2020 STRATEGIC PLAN IMPLEMENTATION

VOL VISION 2020 STRATEGIC PLAN IMPLEMENTATION VOL VISION 2020 STRATEGIC PLAN IMPLEMENTATION CONTENTS Vol Vision 2020 Summary Overview Approach Plan Phase 1 Key Initiatives, Timelines, Accountability Strategy Dashboard Phase 1 Metrics and Indicators

More information

Historical maintenance relevant information roadmap for a self-learning maintenance prediction procedural approach

Historical maintenance relevant information roadmap for a self-learning maintenance prediction procedural approach IOP Conference Series: Materials Science and Engineering PAPER OPEN ACCESS Historical maintenance relevant information roadmap for a self-learning maintenance prediction procedural approach To cite this

More information

POS tagging of Chinese Buddhist texts using Recurrent Neural Networks

POS tagging of Chinese Buddhist texts using Recurrent Neural Networks POS tagging of Chinese Buddhist texts using Recurrent Neural Networks Longlu Qin Department of East Asian Languages and Cultures longlu@stanford.edu Abstract Chinese POS tagging, as one of the most important

More information

Speech Emotion Recognition Using Support Vector Machine

Speech Emotion Recognition Using Support Vector Machine Speech Emotion Recognition Using Support Vector Machine Yixiong Pan, Peipei Shen and Liping Shen Department of Computer Technology Shanghai JiaoTong University, Shanghai, China panyixiong@sjtu.edu.cn,

More information

CAREER SERVICES Career Services 2020 is the new strategic direction of the Career Development Center at Middle Tennessee State University.

CAREER SERVICES Career Services 2020 is the new strategic direction of the Career Development Center at Middle Tennessee State University. CAREER SERVICES 2020 Career Services 2020 is the new strategic direction of the Career Development Center at Middle Tennessee State University. CONTENTS: Background Summary of New Strategic Initiatives

More information

Longest Common Subsequence: A Method for Automatic Evaluation of Handwritten Essays

Longest Common Subsequence: A Method for Automatic Evaluation of Handwritten Essays IOSR Journal of Computer Engineering (IOSR-JCE) e-issn: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 6, Ver. IV (Nov Dec. 2015), PP 01-07 www.iosrjournals.org Longest Common Subsequence: A Method for

More information