Scalability 2018

The competition for machine learning professionals today is fierce, with most practitioners already off the market and the ones that are looking to be hired requiring salaries an average data team simply can't afford. The key to staying in the game? Tooling up your traditional software development teams (those typically focused on programming languages, software technology choices, software quality, development methodologies, code reviews, bugs, etc.) so they can take on deep learning and AI challenges, which require an entirely new set of skills around working with data. In this session, Todd Sundsted, CTO at SumAll, will make the case to invest in your current devops teams by training software developers and engineers the skills they need to take on AI, and will explain the difference in the tools and skills needed to become a machine learning professional, from training vs. coding to replacing traditional methodologies and practices with things like understanding bias in data, dealing with prediction error & drift.