How to solve data related problems in machine learning: The data janitor returns
This down-to-earth machine learning talk from Daniel Molnar is for the underdog. What choices should you make in the vast world of machine learning and deep learning when there are so many options? Don’t base your choices on a gut feeling or product hype; use real world experience based on practical applications.
If you’re trying to solve data related problems with no or limited resources, be them time, money or skills, don’t go no further. This talk is opinionated and deals with GDPR, deep learning, and all the hype. How does data infiltrate the organization? Which roles come first, what problems do they solve and what problems do they introduce? A down-to-earth approach in this hype-driven environment to make decisions impactful and practical-based on real world experience, not product brochures and GitHub repository stars.
Daniel Molnar The Data Janitor, data nerd, and start-up specialist with nineteen years of experience in start-ups and nine in data. Experienced co-founder, built and hired teams up to thirty persons. Proven build-to-market capabilities. Utilizing data for successful products – CS + data + product background under one hat.