How sequential recommendation and representation learning can be leveraged to model customer behavior — By Sam Sharpe, Senior Software Engineer and Karthik Rajasethupathy, Senior Manager, Data Science Digitization has made its way into the financial services industry with the explosion of online services for credit cards, rewards, loans, banking, investing, and budgeting. Innovation in this field has roughly mirrored similar trends in ecommerce, where…

How machine learning methods are evolving to address the complex temporal and sequential elements of consumer financial data — Time series modeling has always been a core element of finance as investment in the financial industry is largely based on some understanding of future economic and market conditions given current and historical knowledge. …

The history of MLB’s pitch classification system and a deep dive into recent enhancements. — Written by Cory Schwartz and Sam Sharpe Introduction When you’re watching your favorite pitcher in your local ballpark, on your local RSN, or on MLB.TV, it’s unlikely that you’d say he threw a pitch at 88 miles per hour with a 2400 RPM spin rate and two inches of vertical movement…

The Baseball Data Machine Learning team is focused on using data to tell the story of baseball and help serve baseball fans and clubs. Our team is constantly learning from the broader data science, machine learning, and sabermetric communities and will share our own experiences through this blog. What is Expected Weighted On-Base Average (xwOBA)? A player’s…