MALO 020 May 29 – Dean Abbott

Dean Abbott, data science and machine learning consultant, a keynote speaker, and author of the book Applied Predictive Analytics talks about the early days of machine learning, what he learned from a dozen years of being Chief Data Scientist at a marketing analytics and automation company, and shares some very astute insights about data in general.

• Demographics, and psychographics can't hold a candle to behavioral data


• The diminishing value of time series data


• Prioritizing data projects


• Ensemble models explained like I'm five


• How many trees you need for a decent random forest


• Periodicity, stationarity, and the naiveté of algorithms


• The value of spending 80% of your time mucking about in the data


• And the two things he'd really like to accomplish in the next 10 years in the industry

Dean is an energetic, engaging, enlightening guest!