New Series on Model Development Automation at Mission Lane

If you work on operational tools and products powered by AI/ML, you may find that deployment in production is highly automated, while the model development process is still frustratingly manual and dominated by prototyping tools like Jupyter notebooks. Automating model development as well doesn’t just help Data Science teams get results more quickly, but also makes those results better and more trustworthy. Over the last year, I’ve been working with Mission Lane’s incredibly talented Data Science team to put this principle into practice. Check out my new series on the Mission Lane Tech Blog on how and why we’ve embraced automated, reproducible model development! 🚀

Part 1, “Why to Automate”, covers the compelling benefits for Data Science teams that invest in automating model development. Part 2, “How to Automate” shows how I helped Mission Lane achieve those benefits with a relatively small investment in open-source software tools.

If this sounds like something that would benefit your team, I’d love to hear from you!