Shipping ML at Scale (for real): Lessons Learned and Best Practices to Successfully Deploy Machine Learning Models

According to TechRepublic, 85% of Machine Learning projects fail. Among the reasons that contribute to this scary statistic the most prominent are lack of leadership support, strategy or engineering skills. In the talk I’ll try to examine the main pain points, explaining best practices on how to overcome these challenges, bringing on the table real world examples, personal experiences and actual insights that allowed me and the teams I worked with to successfully deploy ML at scale and drive a real business impact. More than 15% of the time.