Vybihal Assignment 7 – COMP 273 Page 1 of 4 CPU COMP 273 Assignment 7 – Fall 2021 Due: December 1, 2021, at 4 PM on myCourses Submission instructions All work must be your own and must be submitted to myCourses. Include your name and student number in a comment at the top of your […]
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CS131: Programming Languages DIS 1D Week 9 Winter 2022 Office Hours: Copyright By PowCoder代写 加微信 powcoder Tuesday 8-9pm, Friday 9:30-10:30am Zoom Link on BruinLearn (Same as discussion) Discussion Section: 1D, Fridays 2:00 – 3:50pm Course Announcement • Project due: Next Monday, March 7 • HW6 due: Next Friday, March 11 – No submission allowed after
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COMP3308/COMP3608, Lecture 3a ARTIFICIAL INTELLIGENCE A* Algorithm Reference: Russell and Norvig, ch. 3 Copyright By PowCoder代写 加微信 powcoder , COMP3308/3608 AI, week 3a, 2022 1 • A* search algorithm • How to invent admissible heuristics , COMP3308/3608 AI, week 3a, 2022 2 • UCS minimizes the cost so far g(n) • GS minimizes the estimated
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PowerPoint Presentation Re-cap from Week 8 – Decision Tree Classification and regression tree (continuous and binary variables) The logic of decision-tree algorithm (information entropy; information gain) Model evaluation (Lift, Misclassification, ROC) Model comparison Learning Objectives Describe Automated Machine Learning (AML) Explain why AML is different from traditional data science development Describe the benefits to the
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PowerPoint Presentation Re-Cap from Week 4 Clustering Vs Segmentation Clustering Algorithms Hierarchical K-means Hierarchical Clustering FIGURE 5.2, Vidgen et al. 2019 K-means Clustering FIGURE 5.3, Vidgen et al. 2019 Lecture Outcomes Lecture Outcomes The learning outcomes from this week’s lecture are: Specify a multiple linear regression model Describe the output of a multiple linear regression model Interpret the output
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PowerPoint Presentation Re-Cap from Week 3 – Data Exploration Data Characteristics (Data Types, Cardinality, Data Distribution, Outliers, Missing Data) Chart Types (Bar Chart, Histogram, Line Chart, Scatter Plot, Bubble Chart, Geo Map, Box Plot, Tree Map, Heat Map, Pie Chart) Data Visualization (Benefits, SAS VA demo) Key Principles of Data Visualization Keep your audience in
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PowerPoint Presentation Database Systems Infrastructure Copyright © 2012, SAS Institute Inc. All rights reserved. Today, we will cover the last bit you will learn in this course on Big Data. Now, you see how everything in the diagram is connected. In summary, you have learned normalisation design of the database in Week 4 using ERD,
Chapter 3 Database Systems Infrastructure ©2017 Cengage Learning®. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom
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PowerPoint Presentation Recap from Week 7- Logistic Regression Logistic Regression Model (Probability, Odds, Logit) Model Evaluation (Confusion Matrix, Fit, Lift, ROC) Model Predication (interpret results for categorical variables, making prediction ) Decision Trees Learning Objectives The learning outcomes from this week’s lecture are: Explain how a decision tree works for categorical and continuous outcome variables
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PowerPoint Presentation What is analytics Analytics is the use of: data, information technology, statistical analysis, quantitative methods, and mathematical or computer-based models to help managers gain improved insights about their business operations and make better, fact-based decisions. What if you could… . . . predict the buying behavior and decision criteria of your potential customers