ICT159 Foundations of Programming Assignment 2 DUE : See LMS If you are unsure of anything, you need to get clarification early. So read this document very carefully. OBJECTIVES: • Construct algorithms to solve problems using a combination of sequence, selection and iteration constructs. • Implement such algorithms in a common programming language, C. • […]
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Final Assignment: Part 2 (week 8) Rules for the Final Assignment: Part 2 (week 8) solution • You will upload, on Blackboard, one single file. • The file name, with all functions, must be in the format: .py, e.g.: fdoo1r22.py. This file is the Final Assignment: Part 2 (week 8) solution that will be uploaded
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Last Modified: May 17, 2021 CS 179: Introduction to Graphical Models: Spring 2021 Homework 5 Due Date: Wednesday, May 26th The submission for this homework should be a single PDF file containing all of the relevant code, figures, and any text explaining your results. When coding your answers, try to write functions to encapsulate and
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Assessment Task 2 Stochastic Optimization using Population Based Incremental Learning A/Prof Stuart Perry School of Electrical and Data Engineering, University of Technology Sydney UTS CRICOS 00099F What we will cover 1. Introduction 2. What you have to do 3. How you submit your work 41082 Introduction to Data Engineering Where we are at in the
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COMP20008 Elements of Data Processing Semester 1, 2021 Lecture 8, Part 1: Classification– Introduction Contact: pauline.lin@unimelb.edu.au © University of Melbourne 2021 Classification • Introduction to classification • Comparing Classification and Regression • Decision tree classification • Will make connections to entropy • k nearest neighbour classification © University of Melbourne 2021 Classification • Classification •
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COMP20008 Elements of Data Processing Semester 1 2021 Recommender Systems Plan today • Why recommender systems? • Recommender systems and collaborative filtering – Popularity based – Collaborative filtering – memory based • Item-Item • User-User • Friday’s lecture – Content-based and model-based collaborative filtering – System evaluation Why recommender systems? • Scarcity to Abundance •
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COMP20008 Elements of Data Processing Experimental Design Semester 1, 2021 Chris Ewin Where are we now? 2 Supervised vs Unsupervised Learning 3 Experimental Design • Feature Selection • Dimensionality Reduction • Performance Evaluation 4 Feature Selection 5 Feature selection for machine learning • A series of data wrangling steps result in a set of features
COMP20008 Semester One 2018 Sample Exam The University of Melbourne Semester One 2018 Sample Exam Department: Computing and Information Systems Subject Number: COMP20008 Subject Title: Elements of Data Processing Exam Duration: 2 hours Reading Time: 15 minutes This paper has 6 pages Authorised Materials: No calculators may be used. Instructions to Invigilators: Supply students with
COMP20008 Elements of Data Processing Semester 1, 2021 Lecture 5, 6, Correlation & Clustering – Exercises Contact: pauline.lin@unimelb.edu.au © University of Melbourne 2021 Question 2ai) from 2016 exam a) Richard is a data wrangler. He does a survey and constructs a dataset recording average time/day spent studying and average grade for a population of 1000
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COMP20008 Elements of Data Processing Semester 1 2021 Lecture 4, Part 1 – Part 4: Unstructured Data – Text Preprocessing © University of Melbourne 2021 Text (string) search String Matching and String Comparison © University of Melbourne 2021 Exact string search • Given a string, is some substring contained within it? • Given a string,
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