superkitty
superkitty on Hacker News
Looks like pretty much all high tech company's slowing the hiring. That usually indicates that in few months it would not be surprised to see stating the blood bath in tech companies.
leetcode(eat/drink/sleep) and system design, ML Infra
Interesting..What is Tasker? Do I need to download and configure it on the phone device?
Started building the houses for needy folks!
We use self deployable configuration to allow Data Scientist to control the model's destiny.
Models are written in Python (mix of pytorch/NLP/tensorF).
The Models are serving about 35 predictions/second on avg.
The API server written in the Python. API server container feeds or write the requests in the distributed queue cluster.
The models picks up the samples from the queue in batching.
It allows to experiment the models (different flavor) based on the routing being set during the deployment time and which in turns being set in the cache.
We use AWS managed cache, queuing and container orchestration platform.
Next:
1)Current pipeline for the training and production is two separate pipeline which we want to combined, possibly use MLFlow, Airflow or KubeFlow.
Deployment to the production is done through Jenkins.
2)Active retraining and auto deployment to production.
3)Tie the version of model in production to model being trained. There is no way for us to tie back the version.
What about the A/B testing? What do you use for A/B strategy. How many predictions are being served by the model per second?
Any inputs on Argo workflows vs Kubeflow vs MLFlow? Which is better suited?
What about the A/B testing? What do you use for A/B strategy. How many predictions are being served by the model per second?
thanks for the url, I meant to say Co2 may be.
Posted by
superkitty on Wednesday October 30, 2019 @10:22AM
from the self-post dept.
How is the agtech innovation going on around the US and globe?I noticed there are bunch of startups doing great work and making the planet great by removing the carbon from the soil. How do they apply the ML/DS technique? What sort of the challenging problem their engineering team is solving or intend to solve? Reference: www.indigoag.com
Automating menial work of Fax reading/processing in US healthcare by applying the ML.
I got $1500/month for cleaning houses on weekend.
What folks use for deployment strategy for machine learning based models?
Mesosphere DC/OS, AWS, ECS, EKS, EC2, cloudformation, Jenkins, deployment API developed at home grown...
155K + 15K signing bonus + 25k yearly bonus+ some equity (10% of base salary/4 years = vesting)- Boston, MA Sr SWE