This course is about text mining, its theory, concepts, and applications. Specifically, the course focuses on the acquisition, processing and mining of textual data with KNIME Analytics Platform. You will learn how to use the Text Processing Extension to read textual data into KNIME, enrich it semantically, preprocess it, transform it into numerical data, and extract information and knowledge from it through descriptive analytics (data visualization, clustering) and predictive analytics (regression, classification) methods. Course also covers popular text mining applications including social media analytics, topic detection and sentiment analysis.
- [L1-DS] KNIME Analytics Platform for Data Scientists: Basics - March 30
- [L1-DW] KNIME Analytics Platform for Data Wranglers: Basics - March 30
- [L3-DC] KNIME Server Course: Productionizing and Collaboration - March 30
- [L4-DL] Introduction to Neural Networks and Deep Learning - March 30
- [L4-TS] Introduction to Time Series Analysis - March 30
- [L2-DS] KNIME Analytics Platform for Data Scientists: Advanced - March 31
- [L2-DW] KNIME Analytics Platform for Data Wranglers: Advanced - March 31
- [L3-PC] KNIME Server Course: Productionizing and Collaboration - March 31
- [L4-BD] Introduction to Big Data with KNIME Analytics Platform - March 31
- [L4-ML] Introduction to Machine Learning Algorithms - March 31
- [L4-PR] The Power of Random: Using Perturbation Experiments to Improve Model Accuracy and Interpretation - March 31
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.
None. This course is designed for beginner text miners.
Your own laptop, ideally pre-installed with the latest version of KNIME Analytics Platform, which you can download at knime.com/downloads.
Download the latest free, open source version of knime here: knime.com/download.
You can install the KNIME Textprocessing Extension via drag&drop from the KNIME Hub.