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Introduction to IBM SPSS Modeler Text Analytics (v18.1.1)

  • Tuition USD $1,650 GSA  $1,413.10
  • Reviews star_rate star_rate star_rate star_rate star_half 4097 Ratings
  • Course Code 0A108G
  • Duration 2 days
  • Available Formats Classroom, Virtual
0A108G - Introduction to IBM SPSS Modeler Text Analytics (v18.1.1)

Course Eligible for IBM Digital Badge

This course is available in other formats
Self-Paced
Introduction to IBM SPSS Modeler Text Analytics (v18.1.1) SPVC (0E108G-SPVC)

This course (formerly: Introduction to IBM SPSS Text Analytics for IBM SPSS Modeler (v18)) teaches you how to analyze text data using IBM SPSS Modeler Text Analytics. You will be introduced to the complete set of steps involved in working with text data, from reading the text data to creating the final categories for additional analysis. After the final model has been created, there is an example of how to apply the model to perform churn analysis in telecommunications. Topics include how to automatically and manually create and modify categories, how to edit synonym, type, and exclude dictionaries, and how to perform Text Link Analysis and Cluster Analysis with text data. Also included are examples of how to create resource tempates and Text Analysis packages to share with other projects and other users.

Skills Gained

Please refer to course overview

Who Can Benefit

Users of IBM SPSS Modeler responsible for building predictive models who want to leverage the full potential of classification models in IBM SPSS Modeler.

Prerequisites

- General computer literacy
- Prior completion of Introduction to IBM SPSS Modeler and Data Science (v18.1.1) is recommended.

Course Details

Course Outline

Unit 1 - Introduction to text mining
- Describe text mining and its relationship to data mining
- Explain CRISP-DM methodology as it applies to text mining
- Describe the steps in a text mining project

Unit 2 - An overview of text mining
- Describe the nodes that were specifically developed for text mining
- Complete a typical text mining modeling session

Unit 3 - Reading text data
- Reading text from multiple files
- Reading text from Web Feeds
- Viewing text from documents within Modeler

Unit 4 - Linguistic analysis and text mining
- Describe linguistic analysis
- Describe Templates and Libraries
- Describe the process of text extraction
- Describe Text Analysis Packages
- Describe categorization of terms and concepts

Unit 5 - Creating a text mining concept model
- Develop a text mining concept model
- Score model data
- Compare models based on using different Resource Templates
- Merge the  results with a file containing the customer- s demographics
- Analyze model results

Unit 6 - Reviewing types and concepts in the Interactive Workbench
- Use the Interactive Workbench
- Update the modeling node
- Review extracted concepts

Unit 7 - Editing linguistic resources
- Describe the resource template
- Review dictionaries
- Review libraries
- Manage libraries

Unit 8 - Fine tuning resources
- Review Advanced Resources
- Extracting non-linguistic entities
- Adding fuzzy grouping exceptions
- Forcing a word to take a particular Part of Speech
- Adding non-Linguistic entities

Unit 9 - Performing Text Link Analysis
- Use Text Link Analysis interactively
- Create categories from a pattern
- Use the visualization pane
- Create text link rules
- Use the Text Link Analysis node

Unit 10 - Clustering concepts
- Create Clusters
- Creating categories from cluster concepts
- Fine tuning Cluster Analysis settings

Unit 11 - Categorization techniques
- Describe approaches to categorization
- Use Frequency Based Categorization
- Use Text Analysis Packages to Categorize data
- Import pre-existing categories from a Microsoft Excel file
- Use Automated Categorization with Linguistic-based Techniques

Unit 12 - Creating categories
- Develop categorization strategy
- Fine turning the categories
- Importing pre-existing categories
- Creating a Text Analysis Package
- Assess category overlap
- Using a Text Analysis Package to categorize a new set of data
- Using Linguistic Categorization techniques to Creating Categories

Unit 13 - Managing Linguistic Resources
- Use the Template Editor
- Share Libraries
- Save resource templates
- Share Templates
- Describe local and public libraries
- Backup Resources
- Publishing libraries

Unit 14 - Using text mining models
- Explore text mining models
- Develop a model with quantitative and qualitative data
- Score new data

Appendix A - The process of text mining
- Explain the steps that are involved in performing a text mining project

When does class start/end?

Classes begin promptly at 9:00 am, and typically end at 5:00 pm.

Does the course schedule include a Lunchbreak?

Lunch is normally an hour long and begins at noon. Coffee, tea, hot chocolate and juice are available all day in the kitchen. Fruit, muffins and bagels are served each morning. There are numerous restaurants near each of our centers, and some popular ones are indicated on the Area Map in the Student Welcome Handbooks - these can be picked up in the lobby or requested from one of our ExitCertified staff.

How can someone reach me during class?

If someone should need to contact you while you are in class, please have them call the center telephone number and leave a message with the receptionist.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals, and private on sites. View our group training page for more information.

The training was good but needed the basic skills of maximo before getting deep in the configuration of it.

This is my second course with ExitCertified. This course exceeded my expectations. The teacher was great and the class was fun.

It is very good and very simple instructions. almost to much hand holding.

Instructor, Training material & span of the training is neatly planned.

This course gave me a clearer understanding of the AWS cloud architecture.

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