Introduction to Textual Analysis and Natural Language Processing Workshop

INQUIRE

A weekly workshop over 5 weeks providing guidance on the use of important natural language processing (NLP) methods in finance.  

<p>This workshop provides introductory and intermediate guidance on popular natural language processing (NLP) methods and their application to financial market data. The programme comprises five three-hour sessions designed to introduce participants to the key steps of textual analysis, from extraction and preprocessing through to common machine learning methods and their applications.</p><p>Content is targeted at participants interested in learning more about textual analysis methods and the opportunities they afford, but who are yet to apply NLP techniques on a routine basis. Programming experience in python or R will be an advantage but is not a requirement. (Code and instructions for all example applications will be provided.) The primary objectives of the workshop are to:</p><ul><li>Provide an introduction to the fundaments of textual analysis and natural language processing as applied to financial market data;</li><li>Distinguish between bag-of-words approaches to analysing text and semantic approaches that better reflect meaning and context;</li><li>Provide an introduction to word sense disambiguation methods to support semantic analysis;</li><li>Introduce supervised machine learning approaches for text classification;</li><li>Review topic modelling methods and associated procedures supporting topic selection.</li></ul><h3>Learning outcomes</h3><p>On completion of the workshop, participants will understand:</p><ul><li>How to construct a term document matrix and apply preprocessing methods aimed at reducing redundant dimensionality;</li><li>Commonly applied bag-of-words proxies for constructs such as reading ease, sentiment, text similarity and thematic content, and the strengths and weaknesses associated with each proxy;</li><li>The distinction between bag-of-words approaches to analysing text and semantic approaches that better reflect meaning and context;</li><li>How and when to apply word sense disambiguation methods to support semantic analysis;</li><li>Topic modelling using latent Dirichlet allocation (LDA) and alternative procedures for incorporating domain-specific expertise;</li><li>Approaches to text classification using a suite of popular supervised machine learning classifiers and associated implementation choices.</li></ul><h3>Dates</h3><ul><li>12th November 2020 - 17:00 - 20:00</li><li>18th November 2020 - 17:00 - 20:00</li><li> 25th November 2020 - 17:00 - 20:00</li><li> 2nd December 2020 - 17:00 - 20:00</li><li>10th December 2020 - 17:00 - 20:00</li></ul><p></p><p><strong>Please note your registration details will be passed to Lancaster University </strong></p>

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Introduction to Textual Analysis and Natural Language Processing Workshop

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