In a continued series on all things data, Jerome meets with 8th Light Principal Crafters Myles Megyesi and Pierce Edmiston to talk about machine learning. Along with AI, it's an area of tech that gets a lot of attention and is often spoken about as some mysterious black box that can solve all the problems.
In this discussion, they break apart the black box and the various misconceptions surrounding ML by looking at how it’s implemented in real-world, production-level applications. They also cover the value of having data scientists and engineers working together on machine learning projects, and how all the usual rules and best practices for writing good code still apply.
- (03:13) - Why all the hype?
- (07:39) - Avoiding Rube Goldberg traps
- (12:19) - Using Ml without a data science background
- (17:03) - Document AI - a case study on implementing an ML model
- (24:52) - Knowing the category of your machine learning problem
- (29:15) - Approaching ML like any other framework
- (31:28) - Is data engineering truly a unique skill set?
Myles Megyesi loves design patterns, functional programming, and popcorn. He is an experienced software crafter who enjoys writing software and nurturing its constant growth into something tangible. Throughout his career at 8th Light, he has fulfilled several long-term engagements, focusing on database performance and coordinating distributed services.
Pierce Edmiston combines a background in scientific research and statistics with experience bringing data products from R&D to product systems. He's worked with data teams at many levels of an organization, and he's passionate about bringing quality software tools and practices that enable data science teams to find more insights with more predictable data.
Jerome Goodrich leads amazing software teams to design and develop thoughtful solutions to complex problems as a principal software crafter at 8th Light. He loves pairing strenuous hikes with deep conversations and is always trying to see things clearly and with an open heart. Jerome lives much of his life off of the internet, but he occasionally writes on his website.
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This podcast was produced in partnership with Dante32.