This course focuses on the processing and mining of textual data with KNIME Analytics Platform. Learn how to use the Textprocessing Extension to read textual data in KNIME, enrich it semantically, preprocess it, and transform it into numerical data. The course also demonstrates how to cluster the data, visualize it, or build predictive models.
- Introduction to KNIME
- Reading and Importing Textual Data
- Text Preprocessing, Semantic Enrichment, and Transformation
- Text Classification
- Text Clustering
Please note: We have a new office space (which is very cool!), but we don't have wheelchair friendly access just yet. We apologize for any inconvenience.
Your own laptop, ideally pre-installed with the latest version of KNIME Analytics Platform, which you can download at knime.com/downloads.
You should be familiar with KNIME Analytics Platform and ideally be using it on a regular basis. This course doesn’t provide an introduction to KNIME. We recommend you be at the level of an advanced KNIME user.
The KNIME Workbench
Overview of target workflow
The KNIME Textprocessing Extension
Data Source nodes
Names entity recognition
Preprocessing and filtering
Transformation into Bag of Words and vector representations
Predictive modeling overview
Creating test and training Sets
An example: decision trees
Overview of additional workflows
Q&A to explore previous topics in more detail