Unveiling Insights Through Data Mining: Session with Professor Basu

Jun 22, 2025

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Join Professor Amit Basu for an in-depth exploration of the domain of data mining. Discover key concepts, techniques, and applications in this informative session.

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Unveiling Insights Through Data Mining: Session with Professor Basu

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1. Data MiningSession 1 Professor Amit Basu abasu@smu.edu

2. The Domain of Data Mining

Data Mining: Data

What is Data?. Collection of data objects and their attributesAn attribute is a property or characteristic of an objectExamples: eye color of a person, temperature, etc.Attribute is also known as variable, field, characteristic, or featureA collection of attributes describe an objectObject is

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Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 CSE 572 Data Mining Instructor: Jieping Ye Department of Computer Science and Engineering Arizona State University. What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object

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DATA MINING LECTURE 1

DATA MINING LECTURE 1. Introduction. What is data mining?. After years of data mining there is still no unique answer to this question. A tentative definition:.

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Data Mining Chapter 1

Data Mining Chapter 1. Kirk Scott. Iris virginica. Iris versicolor. Iris setosa. 1.1 Data Mining and Machine Learning. Definition of Data Mining. The process of discovering patterns in data.

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Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to Data Mining by Tan, Steinbach, Kumar. What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object Examples: eye color of a person, temperature, etc.

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Data Mining: P enelitian Data Mining

Data Mining: P enelitian Data Mining. Romi Satria Wahon o romi@romisatriawahono.net http://romisatriawahono.net +6281586220090. Romi Satria Wahono. SD Sompok Semarang (1987) SMPN 8 Semarang (1990) SMA Taruna Nusantara , Magelang (1993)

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Data Mining 1

Data Mining 1. Data Mining is one aspect of Database Query Processing (on the "what if" or pattern and trend end of Query Processing, rather than the "please find" or straight forward end.

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Data Mining Lecture 1

Data Mining Lecture 1. Introduction to Web Mining. What is Web Mining?. Discovering useful information from the World-Wide Web and its usage patterns Applications Web search e.g., Google, Yahoo,… Vertical Search e.g., FatLens, Become,… Recommendations e.g., Amazon.com

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1. Data Mining (or KDD)

1. Data Mining (or KDD). Definition := “Data Mining is the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data” (Fayyad). Let us find something interesting!. Why Mine Data? Scientific Viewpoint.

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Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to PCA (Principal Component Analysis). What is PCA?. Stands for “Principal Component Analysis” Useful technique in many applications such as face recognition, image compression, finding patterns in data of high dimension

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Data Mining: Data

Data Mining: Data. Lecture 3 TIES445 Data mining Nov-Dec 2007 Sami Äyrämö. Data quality. GIGO – Garbage In, Garbage Out Effectiveness of DM exercise depends on the quality of data Data quality concerns individual measurements (records and fields) collections of observations

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Session – I Data Mining : Concepts and Techniques

Session – I Data Mining : Concepts and Techniques. Dr. JULIE M. DAVID Asst. Professor Department of Computer Applications MES College, Marampally, Aluva. Why Data Mining?. The Explosive Growth of Data: from terabytes to petabytes Data collection and data availability

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Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to Data Mining by Tan, Steinbach, Kumar (edited by S. Parthasarathy 3/2007). What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object

759 views • 42 slides

Data Mining: Data

Data Mining: Data. Introduction to Data Mining by Tan, Steinbach, Kumar. What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object Examples: eye color of a person, temperature, etc.

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Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to Data Mining by Minqi Zhou. Precap –What’s Data Mining?. Many Definitions Non-trivial extraction of implicit, previously unknown and potentially useful information from data

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Data Mining

Data Mining. Introduction. What is data mining. The discovery of new information in terms of patterns or rules from vast amounts of data Process of semi-automatically analyzing large databases to find patterns that are: valid: hold on new data with some certainity

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Data Mining: Data

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Data Mining: Data

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