Supervised Learning
Scaled & Efficient Supervised Learning with AutoML
Accelerating time-to-value by automating modeling tasks on beer consumer data—using H2O.ai in R and Python.
An Attribute of a Value-Adding Hybrid Thinker + Doer
Data-Informed Thinking + Doing
Tap into the power of data analysis, ML, deep learning, and computational linguistics for informed decision-making, actionable data-driven strategies, and AI.
Unsupervised Learning
Cluster Up Your Game: A Segmentation & Personalization Recipe
Revealing customer insights and personalizing marketing—with examples of hierarchical clustering in R, Python, and Julia.
Unsupervised Learning
Dish It: How Data Mining Serves Smarter Recommendations
Mining for data patterns to improve dining experiences—with examples of Apriori-based association rules in R, Python, and Julia.
Supervised Learning
Spam Filter 101: Don't Let Junk Texts 'Message' Up Your Day
How a telco restored trust and tamed the spam tsunami—using Naïve Bayes probabilistic classifiers in R, Python, and Julia.
Supervised Learning
Stroke of Insight: How Classification Trees Save Lives
Predicting stroke risks and improving preventive care (and costs)—with examples of classification trees in R, Python, and Julia.
Supervised Learning
Don’t Wing It: Predicting Sales with Regression Trees
Identifying success factors, and making smarter, predictive decisions—with examples of regression trees in R, Python, and Julia.
Supervised Learning
Pop Quiz: Can Linear Regression Optimize Advertising ROI?
Modeling numerical predictions to maximize advertising ROI and sales—with examples of linear regression in R, Python, and Julia.
Analysis & Storytelling
Exploratory Data Analysis on Categorical Data
Univariate, bivariate, and multivariate analyses on the Marvel Comics dataset—with examples in R, Python, and Julia.
Analysis & Storytelling
Univariate, Bivariate, and Multivariate Analyses on Numerical Data
Exploratory data analysis of the PGA golf dataset—with examples in R, Python, and Julia.
Probability & Statistics
Summary Statistics
Extracting an initial overview from the 2000 U.S. Census Bureau data—using R, Python, and Julia.