> minimum standards to get called into interviews.
I am a bit curious on what is the minimum standard? It does feel to me (an outsider that took 1 class of ML in college) that you need at least Master in ML to get intuition on the probabilistic and linear algebra theory behind ML concepts.
Do you have a recommended tutorial for engineer with backend background to setup a simple k8 infra in ec2, I am interested in understanding devops role better
Whats your opinion on postgres vs nosql like cassandra and aerospike, fundamentally is there any reason that postgres can't scale as well as nosql? If I store key value in postgres and add read replica to scale read and partition to scale write will I not be able to keep up with other nosql solutions? If so what are the reasons?
Woah, I didn't know there is an entire ecosystem of contract job and auditors for big projects. How do companies usually hire contract jobs (outsourced HR, upwork, Accenture)? And how do they hire auditors?
might be a dumb question, but how do you render frontend server side? Is the content of the UI dynamically generated in the backend and serve as a static page to users?
Why would they do that tho? Doesn't that encourage fraud and damage their brand? I am just scratching my head trying to understand the benefit of doing that besides logistic cost?
I am confused, if a new model beats randomly selected randomised model 100% of time for each experiment why does it matter if randomised model beats other randomised models? Are they only comparing against the subset of worst randomised models?
Isn't sparse recommendation for videos kind of solved in netflix prize, where the winner uses SVD to extract signature characteristic and recommend videos base on that?
> It's a problem with a thousand solutions. It's just a matter of getting costs down and production up
Can you source this? I heard of molten salt, gravity storage etc... but I have not read any paper stating we can scale those solution to 50% or even 20% of our current grid usage
I am a bit curious on what is the minimum standard? It does feel to me (an outsider that took 1 class of ML in college) that you need at least Master in ML to get intuition on the probabilistic and linear algebra theory behind ML concepts.