W7L148G  Basics of Intelligent Document Processing with IBM Watson Discovery

Duration:    1 Days

Level:          Intermediate

Audience:   Solution Advisor, Data Scientist

Next Sessions
Start (YYYY-MM-DD) End (YYYY-MM-DD) Language Amount
2024-05-10 2024-05-10 English 1250 EUR 1591
2024-05-24 2024-05-24 English 1250 EUR 1605
2024-06-07 2024-06-07 English 1250 EUR 1619
2024-06-21 2024-06-21 English 1250 EUR 1633
2024-07-05 2024-07-05 English 1250 EUR 1647
2024-07-19 2024-07-19 English 1250 EUR 1661
2024-08-02 2024-08-02 English 1250 EUR 1675
2024-08-16 2024-08-16 English 1250 EUR 1689
2024-08-30 2024-08-30 English 1250 EUR 1703
2024-09-13 2024-09-13 English 1250 EUR 1717
2024-09-27 2024-09-27 English 1250 EUR 1731
2024-10-11 2024-10-11 English 1250 EUR 1745
2024-10-25 2024-10-25 English 1250 EUR 1759
2024-11-08 2024-11-08 English 1250 EUR 1773
2024-11-22 2024-11-22 English 1250 EUR 1787
2024-12-06 2024-12-06 English 1250 EUR 1801
2024-12-20 2024-12-20 English 1250 EUR 1815
Overview

This course introduces you to common NLP tasks, Smart Document Understanding, customization of the query results, teach the domain language to Watson Discovery to improve the relevancy and accuracy of the results.

 

Watson Discovery is a cognitive search and content analytics engine that you can add to applications to identify patterns, trends, and actionable insights to drive better decision-making.

Prerequisites

The course requires no prior knowledge of computer programming or machine learning. You are not be required to do any coding to complete the course.  Before taking this course, you should have a Watson Discovery Plus plan.

  • Define the case study 
  • Outline basic NLP tasks and language models in NLP 
  • Define rule-based models and machine learning models in NLP 
  • Define information retrieval and information extraction 
  • Introduce Watson Discovery features for document search 
  • Apply smart document understanding 
  • Modify display of query results 
  • Show how to improve the accuracy of query results
  • Case study
  • NLP basics and language models
  • Information retrieval and extract
  • Rule-based models and machine learning models in NLP
  • Introducing Watson Discovery
  • Project setup
  • Manage your collection
  • Improve and customize
  • Define structure
  • Improve relevance