Analyze your data efficiently with Java
What you'll learn
Understand how to evaluate your data with different types of data analysis techniques
Employ Java tools to visualize data in various formats
Understand multimedia data analysis with Java
Get familiar with various data preprocessing techniques
Know how to implement statistical data analysis techniques using Java APIs
Work with NoSQL database
Understand how to track relationships between entities and identify associations, clusters, and patterns
Work with graphical databases and create a basic graph using the TinkerPop framework
Requirements
Working knowledge on Java is a must.
No specific analysis experience is required.
Description
Data analysis is the process of evaluating data using analytical and logical reasoning to examine each component of the data provided. So, if you're looking forward to master the data analysis techniques with Java, then go for this Learning Path.
Packt's Video Learning Path is a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.
The highlights of this Learning Path are
● Get to know the statistical data analysis techniques and implement them using the popular Java
APIs and libraries
● Learn to perform graph analysis with real-world graph analysis examples
Let's take a quick look at your learning journey. This Learning Path starts off with showing you how to obtain, understand, and evaluate the text. You will then look at different files and learn to apply analysis techniques, so that your software programs can make sense of information to gain valuable insights. You will also learn different methods to analyze text, big data, and other types of multimedia such as image analysis, facial analysis, and pattern recognition.
Next, you will explore various techniques for pre-processing your data. You will learn to apply the basic analysis to your business needs and create time-series predictions. You will then see how to implement statistical data analysis techniques using Java APIs. You will also use JDBC to connect Java to SQL and MySQL databases and learn to work with NoSQL databases.
Moving ahead, you will understand how to track data in a graph form so that you can take advantage of the graph analysis techniques and understand the various graph database components. Next, you will learn how to make a basic graph and view, interact with your graphs, and perform analysis such as cluster detection and statistical calculations. Finally, you will walk through a real-world graph analysis problem using Java to read your email communications and graph them for cluster detection.
By the end of this Learning Path, you will have a strong knowledge on data and graph analysis techniques of Java.
Meet Your Expert
We have the best work of the following esteemed author to ensure that your learning journey is smooth
Erik Costlow was the principal product manager for Oracle's launch of Java 8. His background is in software security analysis, dealing with the security issues that rose to the surface within Java 6 and Java 7. While working on the JDK, Erik applied different data analysis techniques to identify and mitigate ways that threats could propagate through the overall Java platform and overlying applications.
Overview
Section 1: Making Sense of Data with Java
Lecture 1 The Course Overview
Lecture 2 Text Mining
Lecture 3 Sentiment Analysis
Lecture 4 Datasaurus Dozen
Lecture 5 Charts and Graphs
Lecture 6 Charts with Lots of Data
Lecture 7 Time Series Graphs
Lecture 8 Data Versus Big Data
Lecture 9 The Hadoop Framework
Lecture 10 Image Processing
Lecture 11 Facial Analysis
Lecture 12 Pattern Recognition
Section 2: Basic Data Analysis with Java
Lecture 13 The Course Overview
Lecture 14 The Purpose of Data Analysis
Lecture 15 Surveying Data Types and Data Structures
Lecture 16 Data Sets and File Formats
Lecture 17 Generating Test Data
Lecture 18 Pre-processing Data Sets
Lecture 19 Types of Data Analysis Problems
Lecture 20 Java Components
Lecture 21 Business Intelligence
Lecture 22 Time Series Predictions
Lecture 23 Descriptive Statistics
Lecture 24 Random Sampling
Lecture 25 Elementary Probability
Lecture 26 Bayes' Theorem
Lecture 27 Tables and Databases
Lecture 28 MySQL
Lecture 29 Code Using JDBC or JPA
Lecture 30 SQL Versus NoSQL Database Systems
Lecture 31 XML and JSON Data Formats
Lecture 32 Data Conversion
Lecture 33 Selection
Lecture 34 Subsetting
Lecture 35 DateTime APIs in JDK 8
Lecture 36 Resampling
Section 3: Graph Analysis with Java
Lecture 37 The Course Overview
Lecture 38 Terminology
Lecture 39 Graph Analysis Components
Lecture 40 Making a Basic Graph
Lecture 41 Graph Analysis Tools
Lecture 42 Graph Mining Social Networks
Lecture 43 Analysis Primer
Lecture 44 Email Parsing
Lecture 45 Email Communication Graphing
This Learning Path is for novice-to mid-level developers and architects who are familiar with Java programming.
Screenshots

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