Michael is a Machine Learning Consultant and Educator with a technical focus on machine learning and statistical analysis using Python, R, SQL and Shiny. He provides expertise for
machine learning, regression analysis and statistics, text mining and social media analysis, time series analysis, Shiny Web Applications and machine learning applications using frameworks such as Keras and TensorFlow. He is a keen researcher and participant in international machine learning conferences.
Conducted automated financial ratio analysis for companies across a range of industries using Python’s Quandl library.
Identified and reported on undervalued stocks based on free cash flow analysis.
Wrote and edited investment commentaries, statistical analysis white papers, sponsored commentaries, quarterly outlooks and customized RFP response materials.
Developed an extensive video course on the application of data manipulation, regression analysis and machine learning techniques in R with O'Reilly Media.
Instructed students on how to utilize R to conduct extensive data manipulation techniques on datasets with over 750,000 observations.
Worked with a team of 4 video content editors for the creation and production of the relevant course material, with over 2 hours of instructional video for students..
Built time series model using Python for company in the energy industry that allowed for automatic selection of moving average parameters based on RMSE minimisation.
Utilized regression analysis in engineering solutions that influenced traffic policy for a local Canadian government.
Designed an OLS regression model with an autocorrelation feature to identify statistically significant 6.569 units increase in road collisions from adverse weather conditions.
