The course "Text Mining with RapidMiner" is an introduction into knowledge discovery from unstructured data like text documents. It focuses on the necessary preprocessing steps and the most successful methods for automatic text classification (including Naive Bayes and Support Vector Machines, SVM) and text clustering. Many practical exercises for different settings (for example e-mail spam detection, automatical e-mail routing, adaptive personal news filtering, sentiment analysis of text documents like news, web pages, blogs, e-mail, or PDF documents) will enable the participants to transfer the gained knowledge to own text mining problems.

Details

• Course ID: 1101
• Number of days: 2 days
• Location: Dortmund, Germany
• Target audience: users, analysts, developers, administrators
• Previous knowledge: basic knowledge of computer programs and mathematics
• Methods: lectures, discussions, individual and group work, exercises on realistic data. Participants may introduce own work and project specific questions in order to find particular solutions together with the trainer and other participants.
• Content: this course includes a compact introduction into the foundations of data mining and into the software RapidMiner. It addresses beginners and intermediate learners. Topics of this course are
  • Basics of Data Mining with RapidMiner
  • Introduction into Data Mining on Texts
  • Preprocessing of Textual Data: tokenizing, tagging, term frequencies, document frequencies, TFIDF
  • Machine Learning Methods for Text Mining: Naive Bayes and Support Vector Machines
  • Automatic Text Classification
  • Text Clustering
  • Sentiment Analysis of Text Documents
  • Information Extraction and Named Entity Recognition
  Extensive exercises on different data sets will be performed.

Prices

Value added tax (VAT) may have to be added to these prices.