Getting Started with Natural Language Processing in Java

Getting Started with Natural Language Processing in Java

English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 3h 16m | 0.99 GB

Get up and running with Natural Language Processing techniques using Java

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.

What You Will 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
Table of Contents

01 The Course Overview
02 Installation and Setup
03 How NLP is Used
04 Text Processing Tasks
05 Understanding NLP Models
06 Java Support for NLP
07 Extracting Text from a Web Page
08 Using Bliki to Access Wikipedia
09 Accessing Data from Common File Formats
10 Accessing Text from a PDF File
11 Performing Basic Cleaning Operations
12 Removing Stop Words
13 Validating Data
14 Simple Java Tokenizers
15 Specialized Java Tokenizers
16 Applying Stemming and Lemmatization to Text
17 What Makes SBD Difficult
18 Simple Java SBDs
19 Using Specialized SBD APIs
20 Training a SBD Model