Machine Learning and Data Science
Projects involving predictive modeling, ML pipelines, feature engineering, and data-driven decision systems.
What It Is
Machine Learning is A subset of AI focused on systems that learn from data. On this site, it matters because it transfers across technical, operational, and venture work instead of staying trapped in one narrow context.
Learn more: https://en.wikipedia.org/wiki/Machine_learning
Machine Learning Pipeline for Automated Ad Pricing
Before TensorFlow existed, built a continuously-learning SQL-based machine learning system that optimized real-time bid pricing for programmatic advertising —...
Machine learning systems
Pipelines train models on data to produce predictive or generative outputs and improve performance through iteration.
Model serving systems
Infrastructure deploys trained models for real-time or batch inference under latency and scaling constraints.
Scoring Algorithm for Customer Revisit Attribution
Designed, implemented, and tested 150 iterations of a scoring algorithm to determine the likelihood of a customer revisiting a physical store, based on mobile...
Similarity & Clustering Systems
Systems measure likeness between entities using features and distance metrics so they can drive insights, grouping, and product behavior.
Voronoi Regions for International Geofencing
Created an algorithm to build an optimal international geofencing system for hundreds of millions of postal address regions, incorporating feedback from 32...