17spm_L15 Case Study SPM 2017 © Ron Poet Lecture 15 1 Introduction Case Study � South Coast Nautical Supplies sells everything associated with sailing. � They currently have a website that asks the user to ring a number to request a catalogue. � They want to start selling things on their site. SPM 2017 © […]
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PTRL5014 Take-home Assignment General Information This assignment consists of two parts, each requiring a separate submission. Part 1 submission is a single word file, while in part 2, you must combine all matlab files and the word file (containing the figures) into a zip file and upload that. The assignment is marked out of 100
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SE (M) 2017-2018 Lab 2 Modelling with UML – Online Reservations Case Study Please get together in pairs or groups of 2-3 people to work on this lab. Prerequisites: User Requirements Definition A piece of software for a travel agency provide reservations facilities for the people who wish to travel on tours by accessing a
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INFO20003 Database Systems INFO20003 Database Systems 1 INFO20003 Database Systems Lecture 05 Modelling with MySQL Workbench Semester 2 2018, Week 3 Dr Renata Borovica-Gajic INFO20003 Database Systems 2 Coverage • Modelling with MySQL Workbench • Recap & further design – Conceptual Design – Logical Design – Physical Design © University of Melbourne 2018 INFO20003 Database
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COMP9318: Data Warehousing and Data Mining 1 COMP9318: Data Warehousing and Data Mining — L3: Data Preprocessing and Data Cleaning — COMP9318: Data Warehousing and Data Mining 2 n Why preprocess the data? COMP9318: Data Warehousing and Data Mining 3 Why Data Preprocessing? n Data in the real world is dirty n incomplete: lacking attribute
Data Representation for High Dimensional Data Lecture 6: Dimensionality Reduction 1 CMSC5741 Big Data Tech. & Apps. Prof. Michael R. Lyu Computer Science & Engineering Dept. The Chinese University of Hong Kong A Compression Example 2 Outline Motivation SVD CUR Application of SVD and CUR PCA Extension to robust PCA 3 Dimensionality Reduction Motivation Assumption:
PowerPoint Presentation LECTURE 8 Sentment Analysis Arkaitz Zubiaga, 31st January, 2018 2 Sentment analysis: defniton and applicatons. Building a sentment classifer: Unsupervised sentment classifcaton. Supervised sentment classifcaton. Other challenges in sentment classifcaton. LECTURE 8: CONTENTS 3 SENTIMENT ANALYSIS Many names to refer to sentiment analysis: Sentiment classification.
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Chapter 1. Introduction to Data Communications Networks, Security, and Privacy 158.235 A/Prof. Julian Jang-Jaccard Massey University Application Layer Reading: Chapter 2 in the prescribed textbook Outline • Application Architecture • Application Layer Services – The Web: HTTP – Email: SMTP, POP – Other Application-Layer Protocols Application Layer • Layer 5 in the Internet model •
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1.dvi D RA FT Speech and Language Processing: An introduction to natural language processing, computational linguistics, and speech recognition. Daniel Jurafsky & James H. Martin. Copyright c© 2006, All rights reserved. Draft of June 25, 2007. Do not cite without permission. 1 INTRODUCTION Dave Bowman: Open the pod bay doors, HAL. HAL: I’m sorry Dave,
Exercises Level 4: I/O and String Manipulation 4.1: Python Strings 1) Use the following string for each of the below exercises: “ The Python course is the best course that I have ever taken. “: a. Display the length of the string. b. Find the index of the first ‘o’ in the string. c. Trim
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