James Sutton is an ML Engineer focused on helping enterprise bridge the gap between what they have now, and where they need to be to enable production scale ML deployments.
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Timestamps:
0:00 - Intro to Speaker
2:20 - Scope of the coffee session
3:10 - Background of James Sutton
8:28 - One-shots Classifier Algorithm   
12:46 - Why is it a challenge from the engineering perspective with deployment?
19:20 - How to overcome bottlenecks?
30:07 - Vision of your landscape?  
34:45 - Maturity playout
38:48 - Maturity perspective of ML
41:49 - Risk of overgeneralizing system designs patterns
46:10 - Reliability, Speed, Cost
46:46 - Consistency, Availability, Partition Tolerance (CAP Theorem)
47:36 - How do you go about discussing these tradeoffs with your clients?
51: 23 - How would you deal with the PII?
58:50 - Collaborative process with clients
1:00:55 - Wrap up