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Fundamentals of Java Programming for Text Mining and NLP
Rating: 3.5 out of 5(10 ratings)
585 students

Fundamentals of Java Programming for Text Mining and NLP

Learn Java Programming for Text Mining and Natural Language Processing using Stanford NLP
Created byGoh Ming Hui
Last updated 7/2018
English

What you'll learn

  • Developed your own Text Analytics and Text Mining Software using Stanford NLP.

Course content

1 section • 14 lectures • 3h 40m total length

  • Introduction18:21

    Explore the fundamentals of Java programming for text mining and NLP, including high-level versus low-level languages, object-oriented and procedural paradigms, and cross-platform execution.

  • Getting Started5:24

    Install the Java development kit and an integrated development environment, understand the Java virtual machine and Java runtime, and set up debugging and code completion to begin Java programming.

  • Language Essentials I31:45

    this lecture introduces console programming in Java, covering variables, data types, input with scanner, printing, arrays, and a calculator using integers and strings.

  • Language Essentials I Part 211:26

    Explore Java data types and conversions in a console calculator: convert string to numbers with parse methods, convert numbers to strings with toString, and perform basic arithmetic.

  • Language Essentials II24:05

    Explore conditional statements in Java by building a console calculator that performs addition, subtraction, multiplication, and division using if and switch statements, with user input via a scanner.

  • Language Essentials II: Loops13:51

    Explore Java loops, focusing on for and while constructs, with examples that print 0 to 2 and illustrate initialization, condition, and increment.

  • Language Essentials II: Methods12:01

    Explore Java methods fundamentals, including modifiers, return types, parameters, and static concepts, with a summation method in a calculator, string-to-integer conversions, and a view of conditionals, loops, and object-oriented programming.

  • Object Essentials29:59

    Explore object oriented programming in Java by building a console calculator, using classes, objects, constructors, getters and setters, encapsulation, and inheritance to extend a math class into a submission class.

  • Text Mining1:35

    Explore text mining with Java and NLP, covering pre-processing, exploration, classification, feature extraction, dimension reduction, and downloading datasets for predictive modeling with regression, classification, and clustering.

  • Text Mining: Text Data Import23:35

    Learn how to import text data for text mining in Java, creating a project, reading directories and files, and streaming content for preprocessing and classification.

  • Text Mining: Text Transformation7:25

    Explore the text transformation stage and the preprocessor, including converting text to uppercase, lowercase, or title case, and removing whitespace and punctuation to prepare data for analysis.

  • Text Mining: Text Exploration22:38

    Learn text mining and natural language processing by applying stemmer and named-entity recognition with stempel, perform pos tagging, and build simple classifications in a Java workflow.

  • Text Mining: Text Classification17:12

    Practice text classification by training a prediction model on training data, evaluating accuracy with temporal cross-validation, and implementing a classifier workflow with linear regression and machine learning algorithms.

  • Conclusion1:27

    Conclude your journey through fundamentals of Java programming for text mining and NLP by exploring Java libraries for machine learning and seeking further learning resources.

Requirements

  • Computer Knowledge

Description

Why learn Data Analysis and Data Science?


According to SAS, the five reasons are


1. Gain problem solving skills

The ability to think analytically and approach problems in the right way is a skill that is very useful in the professional world and everyday life.


2. High demand

Data Analysts and Data Scientists are valuable. With a looming skill shortage as more and more businesses and sectors work on data, the value is going to increase.


3. Analytics is everywhere

Data is everywhere. All company has data and need to get insights from the data. Many organizations want to capitalize on data to improve their processes. It's a hugely exciting time to start a career in analytics.


4. It's only becoming more important

With the abundance of data available for all of us today, the opportunity to find and get insights from data for companies to make decisions has never been greater. The value of data analysts will go up, creating even better job opportunities.


5. A range of related skills

The great thing about being an analyst is that the field encompasses many fields such as computer science, business, and maths.  Data analysts and Data Scientists also need to know how to communicate complex information to those without expertise.


The Internet of Things is Data Science + Engineering. By learning data science, you can also go into the Internet of Things and Smart Cities.


This course aims to equip the reader with Java programming, Text Mining, and Natural Language Processing fundamentals in a fast and practical way. There will be many examples and explanations that are straight to the point. You will develop your own Text Mining Application at the end course. 

This course will go into Natural Language Processing (NLP) and will look into stopwords removal, lowercase, uppercase, Stanford text classification, import text, and text transformation, Stanford NLP is seldom taught, this course teaches Stanford NLP.

You can look at the following courses to the SVBook Advanced Certificate in Software Development.

SVBook Advanced Certificate in Software Development is given to people who have completed the following courses:

  • - Create Your Calculator: Learn R Programming Basics Fast

  • - Create Your Calculator: Learn Python Programming Basics Fast

  • - Create Your Calculator: Learn C Programming Basics Fast

  • - Create Your Calculator: Learn C# Programming Basics Fast

  • - Create Your Calculator: Learn Java Programming Basics Fast

  • - Create Your WebBrowser: Learn C# Fundamentals Practically

and passed a 50 questions Exam. The six courses are created to help learners understand about programming basics. The learner will be able to program R, Python, C, C#, and Java after the courses


Contents 

1. Introduction 

2. Getting Started (Installing IDE, ...) 

3. Language Essentials I (variables, data types, ...) 

4. Language Essentials II (loops, if... else..., methods) 

5. Object Essentials (classes, inheritance, polymorphism, encapsulation, ...) 

6. Text Mining Essentials (Import Text Files, Text Transformation (lowercase, stopwords), Text Understanding (Stanford NLP), Text Classification (Stanford Classifier) ) 

7. Conclusion 

Who this course is for:

  • Beginner Data Analyst or Data Scientist interested in Data Science, Text Mining, Natural Language Processing, and Stanford NLP

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