Getting Started with Natural Language Processing in Java
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Getting Started with Natural Language Processing in Java

Get up and running with Natural Language Processing techniques using Java
4.0 (1 rating)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
2 students enrolled
Created by Packt Publishing
Last updated 9/2017
English
English [Auto-generated]
Current price: $10 Original price: $125 Discount: 92% off
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Includes:
  • 3.5 hours on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Understand how NLP can be used
  • Explain basic, commonly used NLP tasks
  • Understand how NLP models are created and used
  • Use various techniques to acquire and clean data
  • Perform tokenization based on specific text processing needs
  • Split text into individual sentences
View Curriculum
Requirements
  • This comprehensive video tutorial will get you up-and-running with the basics of using Natural Language Processing Techniques with Java.
Description

Natural Language Processing (NLP) is used in many applications to provide capabilities that were previously not possible. It involves analyzing text to obtain the intent and meaning, which can then be used to support an application. Using NLP within an application requires a combination of standard Java techniques and often specialized libraries frequently based on models that have been trained. You need to know what is available, how these technologies can be used, and when they should be used. In this course we will cover the essence of NLP using Java. This video course will commence by walking you through basic NLP tasks including data acquisition, data cleaning, finding parts of text, and determining the end of sentences. These serve as the basis for other NLP tasks such as classifying text and determining the relationship between text elements. This will be followed by the use of tokenization techniques. Tokenization is used for almost all NLP tasks. You will learn how text can be split to reveal information such as names, dates, and even the grammatical structure of a sentence. These types of activity can lead to insights into the relationships between text elements and embedded meaning in a document. Upon completion of this course, you will be ready to take on more advanced NLP tasks.

About The Author

Richard Reese has worked in the industry and Academia for the past 29 years. For 10 years he provided software development support at Lockheed and at one point developed a C-based network application. He was a contract instructor providing software training to industry for 5 years. Richard is currently an Associate Professor at Tarleton State University in Stephenville, Texas. He has authored the Packt Book: Natural Language Processing with Java. He has covered various text processing issues in his Java for Data Science book. While he has not developed a video course before, he has taught numerous courses where he has gained experience in the structure and flow of courses.

Who is the target audience?
  • This video is aimed at Java developers who wish to learn the basics of NLP. Such developers will be working on applications that can benefit from text analysis, whether from providing more sophisticated processing of user input, or adding analytical capabilities to enhance the user's understanding of an application's data sets. The viewer is assumed to have a working knowledge of Java.
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How NLP is Used
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Text Processing Tasks
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Understanding NLP Models
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Data Acquisition
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Using Bliki to Access Wikipedia
09:49

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Accessing Data from Common File Formats
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Accessing Text from a PDF File
10:41
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Data Cleaning
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The aim of this video is to demonstrate basic text cleaning techniques.

Preview 12:48

The aim of this video is to demonstrate how to remove stop words from text.

Removing Stop Words
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The aim of this video is to demonstrate various validation techniques to clean text.

Validating Data
10:16
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Finding Parts of Text
3 Lectures 31:44

The aim of this video is to demonstrate core Java tokenizers.

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The aim of this video is to demonstrate how to use special tokenizers.

Specialized Java Tokenizers
09:27

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Applying Stemming and Lemmatization to Text
13:18
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Finding Sentences
4 Lectures 42:28

The aim of this video is investigate the complexities of SBD.

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Using Specialized SBD APIs
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Training a SBD Model
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About the Instructor
Packt Publishing
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