Natural Language Processing for the Markets

Three Experienced Stock Traders Talking Business, Consulting Documents and Argue About Data. They Work for a Big Stock Exchange Firm. Office is Full of Displays Showing Infographics and Numbers.

Effective leverage of AI and machine learning requires the intersection of domain knowledge and AI skills. This workshop on natural language processing (NLP) covers key approaches for making sense of text data. The aim of the workshop will be to help finance professionals understand how to frame and think through NLP problems. This will enable them to work effectively with data science teams to create NLP solutions that will benefit investment decisions.  A range of approaches will be discussed including: A general overview to NLP text-mining problems,  Data pre-processing,  Machine Learning Models, Feature Selection, and Testing.  Example implementation examples will be shown.  Also, there will be practical sessions where we work through the steps needed to build an NLP solution.

15 - 16 May 2018


2 days (9am to 5pm)


London, UK – Tower Hotel, London E1


Anne Hsu

Course Fee:

£1890 + VAT


Introduction to Natural Language Learning

  • Overview of NLP problems
  • Overview of Machine Learning tasks for NLP
  • Overview of NLP challenges

Text data representation

  • Data pre-processing
  • Bag of words
  • n-grams
  • Concept/Word Vectors

Brief overview of machine learning models

  • Supervised vs. unsupervised learning
  • Classification models

Training and testing data

  • Obtaining datasets
  • Evaluation of NLP tasks
  • K-fold testing
  • Choosing between models

Feature selection

  • Thesaurus expansion
  • TF-IDF, Information measures
  • Topic Models

Introduction to Python for NLP

  • Overview of main packages for NLP
  • NLTK and main commands
  • SciKit-learn and main commands
  • Example Python Exercise

Research work highlights