Webinar: Application of Supervised Machine Learning techniques on Semi-Structured Social Media data for Classification

Jan19 DMA Webinar

RCG’s Damon Samuel will be presenting a webinar on Thursday, January 19, 2017 at 1PM Eastern, titled, Application of Supervised Machine Learning techniques on Semi-Structured Social Media data for Classification

Overview:

Twitter feeds, LinkedIn profiles, Pinterest descriptions, and other social media outlets are all comprised of consumer generated text data that is not always clean or neatly lines up with the business problem at hand. The good news is, these data tend to have some structure in the forms of hashtags, character limits, personal tagging, or geo-tagging. This data lends itself to classification schemes developed a priori by the business. This webinar will demonstrate the use of a supervised machine learning technique, Naive Bayes, in order to classify social media posts into these segments. Common data cleansing issues will be discussed as well as methods for evaluating the quality of the results. The topics of discussion include:

  • Title in English
  • Refresher on Machine Learning Techniques
  • Structure of Data
  • Sources of Data
  • Teaching the computer to read
  • A few tools that can help
  • Why bother anyway
  • Rehash

Registration:

Register now for this instructive session.

Our Presenter:

Damon Samuel, is Director of Data Science at RCG Global Services brings nearly 20 years of analytical experience to bear. Samuel has built models for numerous industries including Insurance, Automotive, Retail, Credit, Pharmaceuticals, Telecom, Staffing, and Utilities. These models have touched IT, Finance, Marketing, Real Estate, and more. Samuel has been recognized by the Advertising Research Foundation as a top researcher and was a board member for the Marketing Science Institute in 2015, as well as acknowledged in “Profiting from the Data Economy” by David Schweidel.

DMA Analytics Community

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