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Course Skill Level:


Course Duration:

3 day/s

  • Course Delivery Format:

    Live, instructor-led.

  • Course Category:

    Big Data & Data Science

  • Course Code:


Who should attend & recommended skills:

Developers with basic Python and machine learning skills

Who should attend & recommended skills

  • Developers wanting to leverage the various aspects of taxonomies to extract insights from raw text.
  • Skill-level: Foundation-level Taxonomies and Textual Analytics skills for Intermediate skilled team members. This is not a basic class.
  • Machine learning: Basic (1-2 years’ experience)
  • Python: Basic (1-2 years’ experience)

About this course

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.

Skills acquired & topics covered

  • Getting familiar with taxonomies, their types, and applications
  • The role that taxonomies play in textual analytics
  • How textual analysis is used in various industries like banking, hospitality, airline, and more
  • The difference between text-based and transaction-based data processing
  • Ontologies and their use in textual analytics
  • The different types of taxonomies
  • The various ways to customize the taxonomy
  • How to keep a taxonomy updated with new and changed words
  • Build your own taxonomy

Course breakdown / modules

  • Insufficiency of Structured Data
  • Manual Processing
  • Evolution of Textual Analytic Technology

  • Taxonomy Components
  • Taxonomies and Language

  • Hierarchical Taxonomies
  • Networked Taxonomies
  • More Applications of Taxonomies

  • Curated Taxonomies
  • Building Your Own Taxonomy
  • Qualifying the Nouns

  • MoveRemove Processing
  • Taxonomy Customization
  • Word Pairs
  • Transporting the Taxonomy

  • Types of Textual Data
  • Types of Textual Dat

  • Document Fracturing
  • Named Value Processing
  • Supporting Processes

  • 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

  • Sentiment Analysis
  • Negativity Analysis
  • Medical Records

  • Publicly Available Banking Data
  • Comments Collected
  • Textual Disambiguation
  • Secondary Inference Analysis
  • Visualization
  • Interpreting the Dashboard
  • Considering a Single Bank

  • What the Call Center Hears
  • Processing the Narrative
  • Examining the Dashboard
  • Getting to Visualization

  • Voice of the Customer
  • Analyzing Restaurant Feedback