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Author: Richard M Reese; Jennifer L Reese; Alexey Grigorev
Publisher: Birmingham : Packt Publishing, 2017.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Reese, Richard M.
Java: Data Science Made Easy
Birmingham : Packt Publishing,c2017
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Richard M Reese; Jennifer L Reese; Alexey Grigorev
ISBN: 9781788479189 1788479181
OCLC Number: 993765106
Notes: Description based upon print version of record.
Using a HashMap to find multiple modes
Description: 1 online resource (715 p.)
Contents: Cover; Copyright; Credits; Table of Contents; Preface; Module 1: Java for Data Science; Chapter 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 techniquesAssembling the pieces; Summary; Chapter 2: 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 sitesUsing OAuth to authenticate users; Handing Twitter; Handling Wikipedia; Handling Flickr; Handling YouTube; Searching by keyword; Summary; Chapter 3: 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 wordsFinding 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; Chapter 4: 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 graphsCreating pie charts; Creating scatter charts; Creating histograms; Creating donut charts; Creating bubble charts; Summary; Chapter 5: Statistical Data Analysis Techniques; Working with mean, mode, and median; Calculating the mean; Using simple Java techniques to find mean; Using Java 8 techniques to find mean; Using Google Guava to find mean; Using Apache Commons to find mean; Calculating the median; Using simple Java techniques to find median; Using Apache Commons to find the median; Calculating the mode; Using ArrayLists to find multiple modes

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