Text Analytics

OVERVIEW

The course introduces concepts, methods and tools of text analytics.

Actually I learned a lot preprocessing skill in text file.

OBJECTIVES

Understanding the foundations of text analytics.

1. Introduction to various text analytics models and techniques.

2. Workshops and hands-on assignments in text analytics using Python libraries;

3. Discussion of the business applications and the managerial issues surrounding the use of text analytics.

4. Gaining experience in the development and prototype implementation of a text analytics project in a group setting;

5. Development of the ability to solve complex problems in an ill-structured environment in a group setting.

Course Outline (Topical):

• NLTK

  1. Python
  2. Feature extraction; Text Classification; Text clustering

• Text Classification (Python)

• Sentiment Analysis

• TTopic Modeling; NER (Information Extraction)

HWs

HW1 : NLTK

HW2 : Classification

HW3 : Sentiment Analysis

HW4 : Business Case

HW5 Woops ！ is non-coding HW :( SPSS

Very Important Supplements:here

Standford 224n NLP