Machine learning (ML) and artificial intelligence (AI) have revolutionized industries and our daily lives, so why is it that 90% of ML models still never make it to production? 

Credera's CTO Jason Goth and Chief Data Scientist Vincent Yates are discussing the top lessons they've learned over years working with clients in this domain. Here are the 6 practices they recommend for ensuring your AI/ML investments are successful:

1. Take a Design-First Approach
2. Keep it Simple
3. Know the Limitations of Your Data
4. There’s More Engineering in an AI/ML Solutions than AI or ML
5. You Can’t Decompose Modeling Problems Like Software Domains
6. Data Scientists Don’t Know How Much Things Cost