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Turning Text into Gold: Taxonomies and Textual Analytics

  • Course Code: Data Science - Turning Text into Gold: Taxonomies and Textual Analytics
  • Course Dates: Contact us to schedule.
  • Course Category: Big Data & Data Science Duration: 3 Days Audience: This course is geared for those who wants to Leverage the various aspects of taxonomies to extract insights from raw text.

Course Snapshot 

  • Duration: 3 days 
  • Skill-level: Foundation-level Taxonomies and Textual Analytics skills for Intermediate skilled team members. This is not a basic class. 
  • Targeted Audience: This course is geared for those who wants to Leverage the various aspects of taxonomies to extract insights from raw text. 
  • Hands-on Learning: This course is approximately 50% hands-on lab to 50% lecture ratio, combining engaging lecture, demos, group activities and discussions with machine-based student labs and exercises. Student machines are required. 
  • Delivery Format: This course is available for onsite private classroom presentation. 
  • Customizable: This course may be tailored to target your specific training skills objectives, tools of choice and learning goals. 

With businesses operating round the clock, a large amount of data gets generated. This data can be efficiently converted into useful knowledge that can take your business to a higher level. This course introduces you to the concept of taxonomies and how they are used to simplify and understand the text. You’ll explore how to use taxonomies for textual analytics. It begins with a quick history of taxonomies and their earliest usage. You’ll learn about the different types of taxonomies (recursive, networked, hierarchical, and so on. You’ll also learn about ontologies and understand how the ontology becomes a bridge between the worlds of technology and business and commerce. The later lessons of the course show how to find the taxonomies that you need for successful textual analytics, update your taxonomies to include the constantly-changing language, and extract meaningful information from raw text using different tools, such as textual disambiguation, document fracturing, and so on. By the end of this course, you’ll be able to utilize the various aspects of taxonomies for efficient textual analysis. 

Working in a hands-on learning environment, led by our Taxonomies and Textual Analytics expert instructor, students will learn about and explore: 

  • Get familiar with taxonomies, their types, and applications 
  • Explore the role that taxonomies play in textual analytics 
  • Understand how textual analysis is used in various industries like banking, hospitality, airline, and more 

Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below 

  • Understand the difference between text-based and transaction-based data processing 
  • Explore ontologies and their use in textual analytics 
  • Study the different types of taxonomies 
  • Explore the various ways to customize the taxonomy 
  • Discover how to keep a taxonomy updated with new and changed words 
  • Build your own taxonomy 

Audience & Pre-Requisites 

This course is designed for developers wants to leverage the various aspects of taxonomies to extract insights from raw text. 

Pre-Requisites:  Students should have familiar with  

  • Basics of ML  
  • Knowledge of Python is assumed. 

Course Agenda / Topics 

  1. Introduction 
  • Introduction 
  1. Brief History of Taxonomies 
  • Brief History of Taxonomies 
  • Insufficiency of Structured Data 
  • Manual Processing 
  • Evolution of Textual Analytic Technology 
  1. Simple Taxonomies 
  • Simple Taxonomies 
  • Taxonomy Components 
  • Taxonomies and Language 
  1. Complex Taxonomies 
  • Complex Taxonomies 
  • Hierarchical Taxonomies 
  • Networked Taxonomies 
  • More Applications of Taxonomies 
  1. Ontologies 
  • Ontologies 
  1. Obtaining Taxonomies 
  • 5: Obtaining Taxonomies 
  • Curated Taxonomies 
  • Building Your Own Taxonomy 
  • Qualifying the Nouns 
  1. Changing Taxonomies 
  • Changing Taxonomies 
  1. Taxonomies as Databases 
  • Taxonomies as Databases 
  • MoveRemove Processing 
  • Taxonomy Customization 
  • Word Pairs 
  • Transporting the Taxonomy 
  1. Taxonomies and Data Models 
  • Taxonomies and Data Models 
  • Types of Textual Data 
  • Types of Textual Dat 
  1. Textual Analytics 
  • 10: Textual Analytics 
  • Document Fracturing 
  • Named Value Processing 
  • Supporting Processes 
  1. Stage 1 Processing 
  • Stage 1 Processing 
  • Basic Refinements 
  • Custom Variables 
  • Inline Contextualization 
  • Proximity Analysis and Resolution 
  • Stop Word Processing 
  • Associative Word Processing 
  • Homographic Resolution 
  • Alternate Spelling 
  • Acronym Resolution 
  • Stemming 
  • Date Normalization 
  1. Stage 2 Processing 
  • 12: Stage 2 Processing 
  • Sentiment Analysis 
  • Negativity Analysis 
  • Medical Records 
  1. Banking Analytics 
  • 13: Banking Analytics 
  • Publicly Available Banking Data 
  • Comments Collected 
  • Textual Disambiguation 
  • Secondary Inference Analysis 
  • Visualization 
  • Interpreting the Dashboard 
  • Considering a Single Bank 
  1. Call Center Analytics 
  • Call Center Analytics 
  • What the Call Center Hears 
  • Processing the Narrative 
  • Examining the Dashboard 
  • Getting to Visualization 
  1. Hospitality Analytics 
  • Hospitality Analytics 
  • Voice of the Customer 
  • Analyzing Restaurant Feedback 
  1. Airline Analytics 
  • Airline Analytics 
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