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Advanced Intelligent Document Processing with IBM Watson Discovery
Course Description
Overview
Advanced Document Search with IBM Watson Discovery explores intelligent document processing at a deeper level. You learn how to create regular expressions, import rule-based models, customize query results, conduct web crawling, and teach the domain language to Watson Discovery to enhance the relevance and accuracy of your results.
Objectives
- Get data through a web crawl
- Import an existing Smart Document Understanding model to collections
- Apply Teach Domain concepts
- Improve the model performance by using the improve relevance function
- Import rule-based models from Watson Knowledge Studio to Watson Discovery
- Illustrate previewing the application
- Create a Conversation Search project with existing collections
Audience
AI specialists who know natural language processing at an intermediate level
Prerequisites
- Intermediate knowledge of Watson Discovery
- Natural Language and Processing fundamentals
Before taking this course, you should have at least:
Experience with Watson Knowledge Studio is not required, but it is recommended to have it at an intermediate level.
Topics
- Introduction
- Case Study
- Get the data
- Manage collections
- Teach domain concepts
- Improve relevance
- Watson Knowledge Studio (optional)
- Uploading Watson Knowledge Studio models to Watson Discovery
- Previewing the application
- Creating a Conversational Search project
Recognition
When you complete the Instructor-Led version of this course, you will be eligible to earn a Training Badge that can be displayed on your website, business cards, and social media channels to demonstrate your mastery of the skills you learned here.
Learn more about our IBM Watson Badge Program →Related Courses
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This course is eligible for the Advanced Intelligent Document Processing with IBM Watson Discovery - Code: W7L152G
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Self-Paced Training Terms & Conditions
THIS IS A SELF-PACED VIRTUAL CLASS. AFTER YOU REGISTER, YOU HAVE 365 DAYS TO ACCESS THE COURSE.
This is a Self-Paced virtual class; it is intended for students who do not need the support of a classroom instructor. If you feel you would better benefit from having access to a Subject Matter Expert, please enroll in the Instructor-Led version instead. Minimal technical support is provided to address issues with accessing the platform or problems within the lab environment.
Before you enroll, review the system requirements to ensure that your system meets the minimum requirements for this course. AFTER YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT. You are billed for the course when you submit the enrollment form. Self-Paced Virtual Classes are non-refundable. Once you purchase a Self-Paced Virtual Class, you will be charged the full price.
After you receive confirmation that you are enrolled, you will be sent further instructions to access your course material and remote labs. A confirmation email will contain your online link, your ID and password, and additional instructions for starting the course.
Upon receipt of the Order Confirmation Letter which includes your Enrollment Key (Access code); the course begins its twelve (12) month access period. IMPORTANT!!! If your course provides access to a hands-on lab (Virtual Lab Environment), you will have a specific number of days (typically 30 days) on the remote lab platform to complete your hands-on labs. Do not start your lab until you are ready to use your lab time effectively. Time allotted in the virtual lab environment will be indicated once you apply the enrollment key. The self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day.
If the course requires a remote lab system, the lab system access is allocated on a first-come, first-served basis. When you are not using the elab system, ensure that you suspend your elab to maximize your hours available to use the elab system. Note: This does not add additional days to your Lab Environment time frame.
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