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Duration: 2 Days*
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Text mining is a knowledge-intensive process in which a user interacts with a document collection over time with the help of a suite of analysis tools. A document collection can be any grouping of text-based documents. Text Mining seeks to extract valuable information from data sources by identifying and exploring patterns.
This course is designed to provide complete knowledge of text mining operations and preprocessing techniques. Delegates will get an understanding of the text categorisation problem. They will learn about significant algorithms to perform text categorisation. Also, they will learn how to use unlabelled data and evaluate text classifiers.
During this 2-day training, delegates will be equipped with the knowledge of clustering and Information Extraction (IE). Delegates will learn how to access constraints and simple specification filters at the presentation layer. Then, delegates will be introduced to hidden Markov models and maximal entropy Markov models. Post completion of this training, delegates will be able to use MEMM for Information Extraction.
Introduction to Text Mining
Core Text Mining Operations
Text Mining Preprocessing Techniques
Introduction to Clustering
Information Extraction (IE)
Probabilistic Models for IE
Introduction to Link Analysis
There are no prerequisites for attending this course.
Anyone wishes to develop their knowledge and skill-set can attend this course. This course is well-suited for:
Duration: 2 Days*
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"Really good course and well organised. Trainer was great with a sense of humour - his experience allowed a free flowing course, structured to help you gain as much information & relevant experience whilst helping prepare you for the exam"
Joshua Davies, Thames Water
"...the trainer for this course was excellent. I would definitely recommend (and already have) this course to others."
Diane Gray, Shell