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종료된 강좌
빅데이터 (CSED426)
This course studies foundations of big data analytics and exercises using tools and languages.
수강 신청 기간이 아닙니다.
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  • 한국어
  • 12주
  • 1주/4시간
  • 해당없음

This course studies foundations of big data analytics and exercises using tools and languages. Big data is an interdisciplinary field involving multiple disciplines including databases, data mining, and machine learning. This course deals with two perspectives of big data — (1) system perspective, presenting how to store and process big data, and (2) methodology perspective, discussing how to build model from data. In the first half of the course, we study how to store, manage, search and analyze big data by utilizing popularly used solutions such as SQL, MapReduce, Hadoop, and Spark. In the second half, we study representative machine learning and data mining methods such as classification, clustering, recommender system, and link analysis.

강좌 목차

주차 주차
1 Introduction to Big data Introduction
Data models
2 Data Analysis with SQL Relational algebra and SQLite
SQL and Query Processing
3 MapReduce MapReduce 1
MapReduce 2
4 Hadoop Hadoop (HDFS & YARN)
Hadoop (MapReduce Programming)
5 Apache Spark Spark 1
Spark 2
6 NoSQL, Data Measures NoSQL
Data Measures
7 Statistics for Big Data, Data Preprocessing Statistics for Big Data
Data preprocessing
8 Machine Learning I: Fundamentals, Decision Trees, Naive Bayes, Rule Learning, Lazy Learning Fundamentals, Decision Trees
Naive Bayes, Rule Learning, Lazy Learning
9 Machine Learning II: Ensembles, Evaluations, Linear Classification, Artificial Neural Networks Ensembles, Evaluations
Performance Evaluation
Linear Classification, Artificial Neural Network
Support Vector Machine
10 Machine Learning III: Support Vector Machines, Optimization Nonlinear SVM
Multi-class classification, Rank SVM
11 Clustering Basics
Hierarchical methods
Density based methods
Grid based methods
12 Recommender System Recommender system 1
Recommender system 2
Recommender system 3
Recommender system 4


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