STAT318 — Data Mining Dr University of Canterbury, Christchurch, Some of the figures in this presentation are taken from “An Introduction to Statistical Learning, with applications in R” (Springer, 2013) with permission from the authors: G. James, D. Witten, T. Hastie and R. Tibshirani. , University of Canterbury 2020 STAT318 — Data Mining ,1 / […]
CS代考 STAT318 — Data Mining Read More »
STAT318 — Data Mining Dr University of Canterbury, Christchurch, , University of Canterbury 2021 STAT318 — Data Mining ,1 / 28 Association Analysis Association analysis is an unsupervised learning technique that finds interesting associations in large data sets. It is often applied to large commercial data bases, where it is useful for selective marketing. If
CS代考 STAT318 — Data Mining Read More »
Tutorial 6 Machine Learning Motivation Copyright By PowCoder代写 加微信 powcoder Focus more on the project. What kinds of questions can you answer with ML? How to choose the appropriate ML model? If time allows, we will go over an exercise from a previous assignment. Project Analytics/ML Decide what statistics will
CSIT314 Software Development Methodologies Data-driven Software Development Data-driven software development Copyright By PowCoder代写 加微信 powcoder Two perspectives: Developing data-driven software products • E.g. Many Artificial Intelligence (AI) applications are data-driven. • Also referred to as AI Engineering Leveraging software development data to generate insights and build tool support for business analysts, software
CS代考 CSIT314 Software Development Methodologies Read More »
Cloud Computing INFS3208 Background – Big Data Era • “Big Data” has been in use since 1990s. • Data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time. • Reasons of Big Data: – – – Hardware development: Storage (more cheaper),
CS代考 Cloud Computing INFS3208 Read More »
Fundamentals of Machine Learning for Predictive Data Analytics Machine Learning for Predictive Data Analytics What is Predictive Data Analytics? What is ML? How Does ML Work? Underfitting/ Summary What is Predictive Data Analytics? What is Machine Learning? How Does Machine Learning Work? What Can Go Wrong With ML? The Predictive Data Analytics Project Lifecycle: Crisp-DM
CS代考 Predictive Data Analytics Read More »
Contrast Data Mining: Methods and Applications COMP90073 Security Analytics , CIS Semester 2, 2021 Outline • Introduction to Contrast Data Mining • Apriori • FP-Growth • Applications of contrast mining in network traffic analysis and anomaly detection COMP90073 Security Analytics © University of Melbourne 2021 Contrast Data Mining – What is it? [1] Contrast –
CS代写 database data mining algorithm Contrast Data Mining: Methods and Applications Read More »
Graph Anomaly Detection COMP90073 Security Analytics , CIS Semester 2, 2021 Outline • Whygraphs? • Extractingfeaturesfromgraphs • Randomwalk • GraphConvolutionalNetworks(GCNs) COMP90073 Security Analytics © University of Melbourne 2021 All Real-world Data Does Not “Live” on Grid Internet IoT networks COMP90073 Security Analytics © University of Melbourne 2021 Outliers vs. Graph Anomalies • Anomaliesanswerthequestionofwhatisinterestingaboutanetwork • Cannotalwaysbetreatedaspointslyinginamulti-dimensionalspace
CS代考 hbase data mining algorithm Graph Anomaly Detection Read More »
Anomaly Detection in Evolving Data Streams COMP90073 Security Analytics , CIS Semester 2, 2021 Outline • Introductiontodatastreams • Windowingtechniques • HS-Trees • IncrementalLOF(iLOF) – Memory-efficientiLOF(MiLOF) COMP90073 Security Analytics © University of Melbourne 2021 Data Streams Data stream is a sequence of data points, which is continues, unbounded, and nonstationary. • StreamliningAnalysis – Largevolumeofdata – Short/real-timeresponse
IT代写 data mining algorithm Anomaly Detection in Evolving Data Streams Read More »
Subject Overview & Introduction to Cybersecurity COMP90073 Security Analytics Dr. & Dr. , CIS Semester 2, 2021 COMP90073 Security Analytics © University of Melbourne 2021 General Information Lecturers: • Dr , MC Level 3, Room 3.3321, • Dr , Tutor: • Yujing Mark Jiang, Lectures: • Tuesdays and Thursdays, 14:15–15:15pm, Zoom Tutorials: (per your registration)