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Advanced Text and Web Mining Techniques
Date and time
Location
RapidMiner HQ
10 Fawcett Street 5th Floor, Suite 502 Cambridge, MA 02138Refund Policy
Description
Advanced Text and Web Mining Techniques with RapidMiner
Thursday, October 23rd and Friday, October 24th from 8:30 am to 5 pm
A light breakfast, lunch, and afternoon snacks will be provided.
Be sure to check out our Introduction to Data Mining and Predictive Analytics course being held in the same location on October 21 and 22. Register on the same day for each to get a special discount.
Class size for this event is limited to 12 students. If the class is sold out and you wish to be added to a waiting list, contact the event organizer.
This training course 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, Support Vector Machines (SVM), and text clustering.
Many practical exercises for different settings will enable the participants to transfer the knowledge gained to their own text mining problems. Examples include: e-mail spam detection, automatic e-mail routing, adaptive personal news filtering, sentiment analysis of text documents like news, web pages, blogs, e-mail, or PDF documents. Since the class labs are hands-on, performed on the students' own laptops, the students will be taking their actual classwork home with them to jumpstart their application to the real world.
After successfully completing this training, the participants will have the ability to:
- identify techniques for processing unstructured data
- transform textual data into a structured format
- apply different statistical text-processing methods
- perform text classification and text clustering
- work on recent tasks like sentiment analysis or opinion mining
Details
- Target audience: users, analysts, developers, administrators
- Previous knowledge: foundations of data mining, and experience using RapidMiner at least equivalent to Introduction to Data Mining and Predictive Analytics
- Methods: lectures, discussions, individual and group work, exercises on realistic data.
Participants may introduce their own work and project specific questions in order to find particular solutions together with the trainer and other participants. The training course addresses intermediate learners and we recommend visiting the course Introduction to Data Mining and Predictive Analytics.
Topics
- Loading of texts
- Loading from flat files
- Loading from data sets
- Loading from databases
- Loading from process definitions
- Concepts
- Documents
- Tokens
- Visualization
- Visualizing documents and tokens
- High-dimensional visualizations for transformed documents
- Handling unstructured data
- Preprocessing of textual data
- Tokenizing
- Stemming
- Filtering of tokens
- Term frequencies
- Document frequencies
- TF-IDF
- Advanced modeling
- Methods for high-dimensional data
- Support Vector Machines
- Text classification
- Text clustering
- Web Mining
- Crawling the web
- Extracting information from web sites
- Transforming web sites to documents
- Information extraction using XPath or regular expressions
Prerequisites
You must bring a laptop to class (Windows, Mac or Linux OS). For Windows, Java Runtime Environment (JRE) version 7 is required. For Mac and Linux, Java Development Kit (JDK) version 7 is needed. Students will be provided with links to install RapidMiner Studio 6 prior to the class.
Instructor
TBD
Training Facility Logistics
The training will be held in Cambridge, MA at the RapidMiner Headquarters training center. The facility is near the Alewife T (metro) stop and other public transportation. Map and directions.
There are a variety of lodging options locally and in other parts of Cambridge and Boston that are accessible to the facility either on foot, bike, or by public transportation.
The closest reliable public parking is at the Alewife T station. From Alewife to RapidMiner HQ, there is a free public shuttle, but it is only a short walk away (perhaps ten minutes).
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Classes require a minimum of 3 students by October 15 to be held. If there are insufficient registrants, the class may be cancelled and all students will be refunded the full registration fee. Students should organize their travel arrangements accordingly and with this proviso.
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Our Refund Policy: Plans change? We get it. But if you can't make it to the class, please email us at training@rapidminer.com no later than October 15. No refunds will be given after this date.