Big Data. Seifedine Kadry

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Hadoop Distributions Chapter 5 Refresher Conceptual Short Questions with Answers Frequently Asked Interview Questions

      12  6 Big Data Analytics 6.1 Terminology of Big Data Analytics 6.2 Big Data Analytics 6.3 Data Analytics Life Cycle 6.4 Big Data Analytics Techniques 6.5 Semantic Analysis 6.6 Visual analysis 6.7 Big Data Business Intelligence 6.8 Big Data Real‐Time Analytics Processing 6.9 Enterprise Data Warehouse Conceptual Short Questions with Answers

      13  7 Big Data Analytics with Machine Learning 7.1 Introduction to Machine Learning 7.2 Machine Learning Use Cases 7.3 Types of Machine Learning Chapter 7 Refresher Conceptual Short Questions with Answers

      14  8 Mining Data Streams and Frequent Itemset 8.1 Itemset Mining 8.2 Association Rules 8.3 Frequent Itemset Generation 8.4 Itemset Mining Algorithms 8.5 Maximal and Closed Frequent Itemset 8.6 Mining Maximal Frequent Itemsets: the GenMax Algorithm 8.7 Mining Closed Frequent Itemsets: the Charm Algorithm 8.8 CHARM Algorithm Implementation 8.9 Data Mining Methods 8.10 Prediction 8.11 Important Terms Used in Bayesian Network 8.12 Density Based Clustering Algorithm 8.13 DBSCAN 8.14 Kernel Density Estimation 8.15 Mining Data Streams 8.16 Time Series Forecasting

      15  9 Cluster Analysis 9.1 Clustering 9.2 Distance Measurement Techniques 9.3 Hierarchical Clustering 9.4 Analysis of Protein Patterns in the Human Cancer‐Associated Liver 9.5 Recognition Using Biometrics of Hands 9.6 Expectation Maximization Clustering Algorithm 9.7 Representative‐Based Clustering 9.8 Methods of Determining the Number of Clusters 9.9 Optimization Algorithm 9.10 Choosing the Number of Clusters 9.11 Bayesian Analysis of Mixtures 9.12 Fuzzy Clustering 9.13 Fuzzy C‐Means Clustering

      16  10 Big Data Visualization 10.1 Big Data Visualization 10.2 Conventional Data Visualization Techniques 10.3 Tableau 10.4 Bar Chart in Tableau 10.5 Line Chart 10.6 Pie Chart 10.7 Bubble Chart 10.8 Box Plot 10.9 Tableau Use Cases 10.10 Installing R and Getting Ready 10.11 Data Structures in R 10.12 Importing Data from a File 10.13 Importing Data from a Delimited Text File 10.14 Control Structures in R 10.15 Basic Graphs in R

      17  Index

      18  End User License Agreement

      List of Tables

      1 Chapter 1Table 1.1 Differences in the attributes of big data and RDBMS.Table 1.2 Data Mining

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