Teaching Team Unit Co-ordinator & Lecturer: Professor Junbin Gao Consultation hour: Tuesdays 14:00-15:00. Room 4085, H70. 2 Lecturer: Dr Jie Yin Consultation hour: Mondays 15:30 – 16:30 Room 4035, H70. Lecturer: Dr Thang Bui Consultation hour: Wednesdays 14:30 – 15:30 Room 4037, H70. Lectures This unit is offered by the Discipline […]
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About COMP9318 (2018 s1) Wei Wang @ CSE, UNSW February 24, 2018 Wei Wang @ CSE, UNSW About COMP9318 (2018 s1) Introduction Lecturer-in-charge: Prof. Wei Wang School of Computer Science and Engineering Office: K17 507 E-mail: weiw@cse Ext: 9385 7162 http: // www. cse. unsw. edu. au/ ~ weiw Research Interests: Knowledge graph / natural
About COMP9318 (2018 s1) Wei Wang @ CSE, UNSW February 24, 2018 Wei Wang @ CSE, UNSW About COMP9318 (2018 s1) Introduction Lecturer-in-charge: Prof. Wei Wang School of Computer Science and Engineering Office: K17 507 E-mail: weiw@cse Ext: 9385 7162 http: // www. cse. unsw. edu. au/ ~ weiw Research Interests: Knowledge graph / natural
Predictive Analytics – Week 2: Linear Regression and Statistical Thinking Predictive Analytics Week 2: Linear Regression and Statistical Thinking Semester 2, 2018 Discipline of Business Analytics, The University of Sydney Business School QBUS2820 content structure 1. Statistical and Machine Learning foundations and applications. 2. Advanced regression methods. 3. Classification methods. 4. Time series forecasting. Before
Predictive Analytics – Week 1: Introduction to Predictive Modelling Predictive Analytics Week 1: Introduction to Predictive Modelling Semester 2, 2018 Discipline of Business Analytics, The University of Sydney Business School Week 1: Introduction to Predictive Modelling 1. Content structure 2. Introduction 3. Business examples and data 4. Notation 5. Statistical decision theory 6. Evaluating model
Predictive Analytics – Week 2: Linear Regression and Statistical Thinking Predictive Analytics Week 2: Linear Regression and Statistical Thinking Semester 2, 2018 Discipline of Business Analytics, The University of Sydney Business School QBUS2820 content structure 1. Statistical and Machine Learning foundations and applications. 2. Advanced regression methods. 3. Classification methods. 4. Time series forecasting. Before
17spm_L06 Gathering Requirements SPM 2017 © Ron Poet Lecture 6 1 Gathering Requirements is Difficult � Customers/users might have contradictory requirements. � Customers/users might have different priorities. � Customers/users might be unaccustomed to articulating their requirements. SPM 2017 © Ron Poet Lecture 6 2 � Customers/users might propose requirements that are technically infeasible, or too
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Chapter 1: Introduction COMP9313: Big Data Management Lecturer: Xin Cao Course web site: http://www.cse.unsw.edu.au/~cs9313/ 1.‹#› 1 Chapter 1: Course Information and Introduction to Big Data Management 1.‹#› Part 1: Course Information 1.‹#› Course Info Lectures： 6：00 – 9:00 pm (Tuesday) Location: Old Main Building 230 (K-K15-230) Webstream Labs: Weeks 2-13 Consultation (Weeks 1-12): Questions regarding
CMS052 Abstract Data Types & Dynamic Data Structures Assessment 1 School of Computer Science CMP3036M Data Science Page 1 of 2 CMP3036M Data Science Assessment 1 of 2 Criterion Grid 2016 – 2017 Learning Outcome Criterion Pass 2:2 2:1 1st LO1 Critically apply fundamental concepts and techniques in data science Section I: Data Programming Tools
Tips for Assessment Item 1 CMP3036M/CMP9063M Data Science 2016 – 2017 Bowei Chen School of Computer Science University of Lincoln Datasets It should be noted that the datasets are purposefully provided without meaning to ensure that the analysis students do is based entirely on data mining algorithms and not in intuitive understanding. As some students
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