27-29 November, Vilnius

Conference about Big Data, High Load, Data Science, Machine Learning & AI

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AHMED ELRAGAL

Lulea University of Technology, Sweden

AHMED ELRAGAL

Lulea University of Technology, Sweden

Biography

Ahmed Elragal (PhD, MBA, BSc) is a professor of information systems at Luleå University of Technology in Sweden. He has a PhD in Intelligence Decision Support Systems from the University of Plymouth in the UK. He has over fifty research papers and articles published at international conferences and journals. He is the winner of the 2010’s international case study competition on “Business Intelligence”, a prestigious international award. He has over 15 years of consulting experience, focused mainly on enterprise systems and business intelligence. He has helped different regional as well as multinationals organizations [including SAP, Teradata, & Egypt Census Bureau] in the areas of enterprise systems, business intelligence, data mining, big data, analytics, etc.

Workshop

Rapid Miner: Playing with Text

Nowadays, text is everywhere such as: enterprise records, consumer complaints, product inquiries; social media; & product reviews. Text is just another form of data, and text processing is just a special case of data representation. Since we, humans, communicate via text, so understanding text is essential for us. However, text is referred to as “unstructured” data. Indeed, text has plenty of structure, but it is linguistic structure— intended for human consumption, not for machines. Therefore, it is difficult to evaluate any particular word or phrase without considering the context, on which it was written. In this session, we learn various things about text analytics.

Agenda

  • Background
  • The essential terminology
  • Preprocessing text
  • Tokenization
  • Bag of Words
  • TFIDF
  • N-grams
  • Sentiment Analysis
  • Topic Modeling
  • Use Cases:
    • A: understanding, pre-processing, & Identifying Text
    • B: Detecting & Classifying Text
    • C: Analyzing Ratings and/or Reviews

Course objectives

During this session, you will get to know about text and how they are important to big data and data science in general. Added to that, you will also run some exercises and scenarios to analyze text using Rapid Miner Software. The session will enable you to tap into the lucrative text analytics domain.

Target audience

The session is designed for data analysts, text analysts, data scientists, and researchers who are pursuing text analytics projects. 

Course prerequisites

Knowledge of data mining + a PC installed on it latest Version of Rapid Miner.

DATE:
27 November, 2018

TIME:
10:00-17:30

Venue to be confirmed

RESERVE YOUR SEAT

DATE:
27 November, 2018

TIME:
10:00-17:30

Venue to be confirmed

RESERVE YOUR SEAT