Java：Data Science Made Easy

coverpage

Title Page

Credits

Preface

What this learning path covers

What you need for this learning path

Who this learning path is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

Module 1

Getting Started with Data Science

Problems solved using data science

Understanding the data science problem - solving approach

Using Java to support data science

Acquiring data for an application

The importance and process of cleaning data

Visualizing data to enhance understanding

The use of statistical methods in data science

Machine learning applied to data science

Using neural networks in data science

Deep learning approaches

Performing text analysis

Visual and audio analysis

Improving application performance using parallel techniques

Assembling the pieces

Summary

Data Acquisition

Understanding the data formats used in data science applications

Overview of CSV data

Overview of spreadsheets

Overview of databases

Overview of PDF files

Overview of JSON

Overview of XML

Overview of streaming data

Overview of audio/video/images in Java

Data acquisition techniques

Using the HttpUrlConnection class

Web crawlers in Java

Creating your own web crawler

Using the crawler4j web crawler

Web scraping in Java

Using API calls to access common social media sites

Using OAuth to authenticate users

Handing Twitter

Handling Wikipedia

Handling Flickr

Handling YouTube

Searching by keyword

Summary

Data Cleaning

Handling data formats

Handling CSV data

Handling spreadsheets

Handling Excel spreadsheets

Handling PDF files

Handling JSON

Using JSON streaming API

Using the JSON tree API

The nitty gritty of cleaning text

Using Java tokenizers to extract words

Java core tokenizers

Third-party tokenizers and libraries

Transforming data into a usable form

Simple text cleaning

Removing stop words

Finding words in text

Finding and replacing text

Data imputation

Subsetting data

Sorting text

Data validation

Validating data types

Validating dates

Validating e-mail addresses

Validating ZIP codes

Validating names

Cleaning images

Changing the contrast of an image

Smoothing an image

Brightening an image

Resizing an image

Converting images to different formats

Summary

Data Visualization

Understanding plots and graphs

Visual analysis goals

Creating index charts

Creating bar charts

Using country as the category

Using decade as the category

Creating stacked graphs

Creating pie charts

Creating scatter charts