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Java Data Analysis

更新時間：2021-07-02 18:22:09

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IfyouareastudentorJavadeveloperorabuddingdatascientistwhowishestolearnthefundamentalsofdataanalysisandlearntoperformdataanalysiswithJava,thisbookisforyou.Somefamiliaritywithelementarystatisticsandrelationaldatabaseswillbehelpfulbutisnotmandatory,togetthemostoutofthisbook.AfirmunderstandingofJavaisrequired.

目錄(133章)

倒序

封面
書名頁
Java Data Analysis
Credits
About the Author
About the Reviewers
www.PacktPub.com
eBooks discount offers and more
Customer Feedback
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Chapter 1. Introduction to Data Analysis
Origins of data analysis
The scientific method
Actuarial science
Calculated by steam
A spectacular example
Herman Hollerith
ENIAC
VisiCalc
Data information and knowledge
Why Java?
Java Integrated Development Environments
Summary
Chapter 2. Data Preprocessing
Data types
Variables
Data points and datasets
Relational database tables
Hash tables
File formats
Generating test datasets
Summary
Chapter 3. Data Visualization
Tables and graphs
Time series
Java implementation
Moving average
Data ranking
Frequency distributions
The normal distribution
The exponential distribution
Java example
Summary
Chapter 4. Statistics
Descriptive statistics
Random sampling
Random variables
Probability distributions
Cumulative distributions
The binomial distribution
Multivariate distributions
Conditional probability
The independence of probabilistic events
Contingency tables
Bayes' theorem
Covariance and correlation
The standard normal distribution
The central limit theorem
Confidence intervals
Hypothesis testing
Summary
Chapter 5. Relational Databases
The relation data model
Relational databases
Foreign keys
Relational database design
Summary
Chapter 6. Regression Analysis
Linear regression
Polynomial regression
Summary
Chapter 7. Classification Analysis
Decision trees
Bayesian classifiers
Logistic regression
Summary
Chapter 8. Cluster Analysis
Measuring distances
The curse of dimensionality
Hierarchical clustering
Summary
Chapter 9. Recommender Systems
Utility matrices
Similarity measures
Cosine similarity
A simple recommender system
Amazon's item-to-item collaborative filtering recommender
Implementing user ratings
Large sparse matrices
Using random access files
The Netflix prize
Summary
Chapter 10. NoSQL Databases
The Map data structure
SQL versus NoSQL
The Mongo database system
The Library database
Java development with MongoDB
The MongoDB extension for geospatial databases
Indexing in MongoDB
Why NoSQL and why MongoDB?
Other NoSQL database systems
Summary
Chapter 11. Big Data Analysis with Java
Scaling data striping and sharding
Google's PageRank algorithm
Google's MapReduce framework
Some examples of MapReduce applications
The WordCount example
Scalability
Matrix multiplication with MapReduce
MapReduce in MongoDB
Apache Hadoop
Hadoop MapReduce
Summary
Appendix A. Java Tools
The command line
Java
NetBeans
MySQL
MySQL Workbench
Accessing the MySQL database from NetBeans
The Apache Commons Math Library
The javax JSON Library
The Weka libraries
MongoDB
Index 更新時間：2021-07-02 18:22:09

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Java Data Analysis