Last updated 1/2018MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 568.53 MB | Duration: 5h 48m

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 muldia 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 muldia 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 -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 Sennt Analysis

Lecture 4 Datasaurus Dozen

Lecture 5 Charts and Graphs

Lecture 6 Charts with Lots of Data

Lecture 7 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 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 Date APIs in JDK 8

Lecture 36 Resampling

Section 3: Graph Analysis with Java

Lecture 37 The Course Overview

Lecture 38 Teology

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 Pr

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.