PPT-Data Mining: Data Lecture Notes for Chapter 2

Introduction to Data Mining 2 nd Edition by Tan Steinbach Kumar Outline Attributes and Objects Types of Data Data Quality Similarity and Distance Data Preprocessing What is Data Collection of . And 57375en 57375ere Were None meets the standard for Range of Reading and Level of Text Complexity for grade 8 Its structure pacing and universal appeal make it an appropriate reading choice for reluctant readers 57375e book also o57373ers students Slide . 1. <. p>Sample . <b>bold</b> display</p>. P. B. #text. #text. nextSibling. prevSibling. nextSibling. prevSibling. firstChild. lastChild. parentNode. parentNode. parentNode. Slide . 1. Basic Ruby Syntax. sum = 0. i. = 1. while. . i. <= 10 . do. sum += . i. *. i. . i. = . i. + 1. end. puts "Sum of squares is #{sum}\n". Newline is statement separator. do ... end. Slide . 1. Basic Ruby Syntax. sum = 0. i. = 1. while. . i. <= 10 . do. sum += . i. *. i. . i. = . i. + 1. end. puts "Sum of squares is #{sum}\n". Newline is statement separator. do ... end. Slide . 1. Google Datacenter. CS 142 Lecture Notes: Datacenters. Slide . 2. Datacenter Organization. Rack:. 50 machines. DRAM: 800-3200GB @ 300 . µs. Disk: 100TB @ 10ms. Single server:. 8-24 cores. DRAM: 16-64GB @ 100ns. Emre Eftelioglu. 1. What is Knowledge Discovery in Databases?. Data mining is actually one step of a larger process known as . knowledge discovery in databases. (KDD).. The KDD process model consists of six phases. Slide . 1. <. p>Sample . <b>bold</b> display</p>. P. B. #text. #text. nextSibling. prevSibling. nextSibling. prevSibling. firstChild. lastChild. parentNode. parentNode. parentNode. Slide . 1. Access Matrix. File A. File B. File C. Printer 1. Alice. RW. RW. RW. OK. Bob. R. R. RW. OK. Carol. RW. David. RW. OK. Faculty. RW. RW. OK. CS 140 Lecture Notes: Protection. Slide . 2. Access Matrix. Iris . virginica. 2. Iris . versicolor. 3. Iris . setosa. 4. 1.1 Data Mining and Machine Learning. 5. Definition of Data Mining. The process of discovering patterns in data.. (The patterns discovered must be meaningful in that they lead to some advantage, usually an economic one.). Iris . virginica. 2. Iris . versicolor. 3. Iris . setosa. 4. 1.1 Data Mining and Machine Learning. 5. Definition of Data Mining. The process of discovering patterns in data.. (The patterns discovered must be meaningful in that they lead to some advantage, usually an economic one.). with an . Eclipse . Attack. With . Srijan. Kumar, Andrew Miller and Elaine Shi. 1. Kartik . Nayak. 2. Alice. Bob. Charlie. Emily. Blockchain. Bitcoin Mining. Dave. Fairness: If Alice has 1/4. th. computation power, she gets 1/4. Slide . 1. CSS Rule. body {. font-family: Tahoma, Arial, sans-serif;. color: black;. background: white;. margin: 8px;. }. Selector. Declaration. Block. Attribute Name. Value. CS 142 Lecture Notes: CSS. Slide . 1. Basic Ruby Syntax. sum = 0. i. = 1. while. . i. <= 10 . do. sum += . i. *. i. . i. = . i. + 1. end. puts "Sum of squares is #{sum}\n". Newline is statement separator. do ... end. . SYFTET. Göteborgs universitet ska skapa en modern, lättanvänd och . effektiv webbmiljö med fokus på användarnas förväntningar.. 1. ETT UNIVERSITET – EN GEMENSAM WEBB. Innehåll som är intressant för de prioriterade målgrupperna samlas på ett ställe till exempel:.