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Java for Data Science

You're reading from   Java for Data Science Examine the techniques and Java tools supporting the growing field of data science

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Product type Paperback
Published in Jan 2017
Publisher Packt
ISBN-13 9781785280115
Length 386 pages
Edition 1st Edition
Languages
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Authors (2):
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Jennifer L. Reese Jennifer L. Reese
Author Profile Icon Jennifer L. Reese
Jennifer L. Reese
Richard M. Reese Richard M. Reese
Author Profile Icon Richard M. Reese
Richard M. Reese
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with Data Science 2. Data Acquisition FREE CHAPTER 3. Data Cleaning 4. Data Visualization 5. Statistical Data Analysis Techniques 6. Machine Learning 7. Neural Networks 8. Deep Learning 9. Text Analysis 10. Visual and Audio Analysis 11. Mathematical and Parallel Techniques for Data Analysis 12. Bringing It All Together

Summary

In this chapter, we demonstrated many techniques for processing speech and images. This capability is becoming important, as electronic devices are increasingly embracing these communication mediums.

TTS was demonstrated using FreeTSS. This technique allows a computer to present results as speech as opposed to text. We learned how we can control the attributes of the voice used, such as its gender and age.

Recognizing speech is useful and helps bridge the human-computer interface gap. We demonstrated how CMUSphinx is used to recognize human speech. As there is often more than one way speech can be interpreted, we learned how the API can return various options. We also demonstrated how individual words are extracted, along with the relative confidence that the right word was identified.

Image processing is a critical aspect of many applications. We started our discussion of image processing by use Tess4J to extract text from an image. This process is sometimes referred to as OCR. We...

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