Asst. Prof. Sotarat Thammaboosadee, Ph.D.

Slides:



Advertisements
Similar presentations
1 Bulgarian policy on Macedonian migration after 1989 Maria Barzinska PhD student New Bulgarian University Department Political Sciences CERMES Academic.
Advertisements

Kensington Oracle Edition: Open Discovery Workflow Meets Oracle 10g Professor Yike Guo.
From choice, a world of possibilities Service Statistics What to do when you can’t locate a service.....
1 Copyright Jiawei Han; modified by Charles Ling for CS411a/538a Data Mining and Data Warehousing  Introduction  Data warehousing and OLAP for data mining.
Polarity Dictionary: Two kinds of words, which are polarity words and modifier words, are involved in the polarity dictionary. The polarity words have.
Introduction to WEKA Aaron 2/13/2009. Contents Introduction to weka Download and install weka Basic use of weka Weka API Survey.
Presented To: Madam Nadia Gul Presented By: Bi Bi Mariam.
ACE TESOL Diploma Program – London Language Institute OBJECTIVES You will understand: 1. The difference between a course, curriculum, and syllabus. 2.
Data Mining: Concepts & Techniques. Motivation: Necessity is the Mother of Invention Data explosion problem –Automated data collection tools and mature.
CSC 177 Research Paper Review Chad Crowe. A Microeconomic Data Mining Problem: Customer-Oriented Catalog Segmentation Authors: Martin Ester, Rong Ge,
IGP Reflection: Evaluate Please update your tracking charts based on the implementation of the paragraph planning from last week. IGP Reflection Questions:
Kansas State University Department of Computing and Information Sciences CIS 830: Advanced Topics in Artificial Intelligence From Data Mining To Knowledge.
Data Mining Techniques As Tools for Analysis of Customer Behavior
Custom driven scientific information extraction from digital libraries using integrated text mining services Betim Çiço, Adrian Besimi, Visar Shehu 14th.
How to get the most out of the survey task + suggested survey topics for CS512 Presented by Nikita Spirin.
Most of contents are provided by the website Introduction TJTSD66: Advanced Topics in Social Media Dr.
Final Project and Term Paper Requirements Qiang Yang, MTM521 Material.
Data Warehousing Lecture-30 What can Data Mining do? Virtual University of Pakistan Ahsan Abdullah Assoc. Prof. & Head Center for Agro-Informatics Research.
REPORTS By Preeti Patel Lecturer School of Library And Information Science DAVV, Indore
October 2-3, 2015, İSTANBUL Boğaziçi University Prof.Dr. M.Erdal Balaban Istanbul University Faculty of Business Administration Avcılar, Istanbul - TURKEY.
Introduction to Data Mining by Yen-Hsien Lee Department of Information Management College of Management National Sun Yat-Sen University March 4, 2003.
DR. SATISH NARGUNDKAR GEORGIA STATE UNIVERSITY Analytics Overview.
Sotarat Thammaboosadee, Ph.D. EGIT563- Data Mining Individual Project Specification 1.
Sotarat Thammaboosadee, Ph.D. EGIT563- Data Mining Course Outline.
1 SBM411 資料探勘 陳春賢. 2 Lecture I Class Introduction.
Zohreh Raghebi.  A software platform provides an integrated environment  Machine learning  Data mining  Text mining  Predictive analytics  Business.
For More Tutorials AED 202 ENTIRE COURSE  AED 202 Week 1 CheckPoint Characteristics of Developmental Periods  AED 202 Week 1 DQ.
AP Computer Science Principals Course Importance and Overview
Information Modeling and Database System
Mental Aspects of Sport Performance
Business Intelligence Minor
Presented by Khawar Shakeel
CSC 321: Data Structures Fall 2016
Writing the Analytical Paragraph
Profiling based unstructured process logs
Eick: Introduction Machine Learning
Get a jump start on your studies
Core Methods in Educational Data Mining
CIS 500 Competitive Success-- snaptutorial.com
MTH 216 Competitive Success-- snaptutorial.com
MTH 216 Education for Service-- snaptutorial.com
CIS 500 Education for Service-- snaptutorial.com
MTH 216 Teaching Effectively-- snaptutorial.com
CIS 500 Teaching Effectively-- snaptutorial.com
Data Mining: Concepts and Techniques Course Outline
Machine Learning & Data Science
Class Notes (5/2/2016) Today Air Pollution (Chp 14)
机器感知与智能教育部重点实验室学术报告 Key Laboratory of Machine Perception (Minister of Education) Peking University Scalable, Robust and Integrative Algorithms for Analyzing.
Data Warehousing and Data Mining
Prepared by: Mahmoud Rafeek Al-Farra
Using Film Techniques as Evidence
Final Project Discussion
Immigration Read the article “Who’s Coming to America” and mark the text appropriately. Create a timeline showing the history of immigration to the United.
Log In to SciQuest.
Immediate activity Gender and subject choice brain dump, without looking at your books or notes write down as much as you can in connection to gender and.
Getting Results with Be Clear and Concise.
Design Brief.
Do Now Log onto the class website
Data Warehousing Data Mining Privacy
4 Greatest Attributes Ready Junior English.
Christoph F. Eick: A Gentle Introduction to Machine Learning
Sentiment Analysis In Student Learning Experience By Obinna Obeleagu
Sentiment Analysis In Student Learning Experience By Obinna Obeleagu
-Tuesday: Review the three p’s -Wednesday: Create an evidence
Title Cover Page You can add slides to print your title in larger text if needed but remove after. This page is for teacher and should not be on the board!
Last Nine Weeks Project
National Curriculum Assessments 2019
CSE591: Data Mining by H. Liu
Insert Title Here Name, Course, Term INTRODUCTION Problem Description
Insert Title Here Name, Course, Term INTRODUCTION Problem Description
Presentation transcript:

Asst. Prof. Sotarat Thammaboosadee, Ph.D. EGIT532- Data Science and Big Data Analytics Individual Project Specification Asst. Prof. Sotarat Thammaboosadee, Ph.D.

Project Individual Project. Submit report in pdf via email. zotarat@gmail.com Before 12 May 2019 Email subject: project-61xxxxx

Topics Problems Source of Data Data Mining Tasks Data Mining Process Business understanding Data understanding Data preprocessing Model building Model Evaluation Deployment

Problems What are the motivations to apply data science with your data?

Source of Data Any data sources At least 10,000 examples At least 8 attributes or text data But if you take more concentration for this stage, it may be a part of your thesis/thematic paper.

Data Mining Tasks Classification Clustering Association Etc…. What? Why? Association Etc….

Business Understanding Provide some paragraph to introduce your work.

Presentation Please provide one or more flow chart of your data mining process. You may capture the Rapidminer workflow Please rename each box in a meaningful name

Data Understanding Type of each attributes Example data set Meaning? Statistical report Data profile Visualization

Data preprocessing More than one method State the reason why you choose them. Data visualization or profiling of each processing step

Model building More than one algorithm Maybe several algorithm in one model, depend on your design More (reasonable) complex process will get more points

Model Evaluation Compare between each preprocessing method and each algorithm Select appropriate criteria

Deployment What do you obtain from the results? Using visualization Knowledge Application Policy Etc…