prabhatjha

9 ms·

31.
by prabhatjha 6y ago
Agree. You don't want to do Fashion Driven Development (FDD). You would end up chasing every shiny thing that comes out and not really master anything. Pick any one stack, build some simple projects and then expand on it. You would als
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Taming Callback Pyramids in AnuglarJS App Using Async/Await(engineering.wootric.com)
14 points by prabhatjha 6y ago|2 comments
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Some recommendations for a fully virtual hiring process(prabhatkjha.com)
2 points by prabhatjha 6y ago|0 comments
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by prabhatjha 6y ago
I am assuming you are talking about our deployment on GCP Cloud Run? We have thought about sending a heartbeat API call. It we notice any user experience friction because of this lag then we will definitely do that. As we said in the blog,
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by prabhatjha 6y ago
We supported batch api calls in v0. But as those API calls increased a new instanced would get spun up but boot time was longer. To get around it, we would have to keep more instances running all the time which obviously costs more money.
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by prabhatjha 6y ago
Thanks for the tips. Having everything colocated in a k8s cluster will definitely help with latency and probably overall infra cost but it will be at the expense of engineering times spent on running a k8s cluster in prod. Fingers crossed t
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by prabhatjha 6y ago
Totally. We did not have a need for custom models initially. We could load all our models on one VM so there was no need. We were tempted to get on the bandwagon. ;-)
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by prabhatjha 6y ago
Because we were loading all the models startup time was long which meant that server would return 5xx errors which created more instability. We would had to do some engineering around it with a mix of config and code changes. The bigger iss
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Wootric moved ML deployment pipeline from AWS to GCP(engineering.wootric.com)
28 points by prabhatjha 6y ago|17 comments
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Mobile app perf monitoring dream and Envoy Mobile(prabhatkjha.com)
2 points by prabhatjha 7y ago|0 comments
41.
Code Walkthrough of Bert with PyTorch for a Multilabel Classification in NLP(engineering.wootric.com)
13 points by prabhatjha 7y ago|2 comments
42.
Custom machine learning model and pipeline deployment on GCP AI Platform(engineering.wootric.com)
14 points by prabhatjha 7y ago|0 comments
43.
Understanding and explaining accuracy in machine learning systems(engineering.wootric.com)
12 points by prabhatjha 8y ago|5 comments
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by prabhatjha 8y ago
I think that AWS are the "bad guy" here. I am happy to be proven wrong but they don’t have a track record of contributing code to the OSS projects they provide as a service. Whenever they are forced like it was the case with Mongo
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by prabhatjha 8y ago
I totally agree. Deploying microservices and running k8s sound easy until you actually do it. For example, just see this section of k8s docs about exposing services: https://kubernetes.io/docs/concepts/services-net
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Comparing AWS and GCP NLP API for Sentiment Analysis and a Case for Custom Model(engineering.wootric.com)
12 points by prabhatjha 8y ago|4 comments
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by prabhatjha 8y ago
This is a great paper. It helped us think more rationally and helped us realize that we were not alone having difficulties running ML in production.
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by prabhatjha 8y ago
Working for a early stage startup depends on the stage of life, your financial freedom and your ability to hustle. Early stage startup requires that you work a lot more than 40 hours of week with a big pay cut compared to what you would get
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by prabhatjha 8y ago
I would also recommend Camille Fournier's The Managers Path book for folks in tech. You will be able to relate to this book whether you are an individual contributor or seasoned manager.
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by prabhatjha 8y ago
Thank you for the link to the paper. We had not come across that one.
51.
by prabhatjha 8y ago
I totally agree with this. We learned it pretty quickly that classification does not generalize across domains so we narrowed the problem space by focusing one domain at a time followed by predefined and fixed set of categories so that we c
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by prabhatjha 8y ago
Got it. Yes, topic classification does not generalize across domains based on what we see in on our implementation.
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by prabhatjha 8y ago
Ah -- I thought you were talking about classification of these tweets so that politicians know what their followers are talking about. Sentiment analysis is a very small part of what we do and as you said there are tons of examples on web t
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by prabhatjha 8y ago
Forget about other languages, it's sometimes tricky for English as well. Someone said language is the world's oldest API but it's also the most complicated. ;-) For couple of our Norwegian and Spanish customers we hit Google
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by prabhatjha 8y ago
That's a great idea. Once we have training data for a new category it does not take us a long time to create a ML model for it. Are you aware of any such corpus? ;-)
56.
Our machine learning and NLP journey(wootric.com)
114 points by prabhatjha 8y ago|27 comments
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Announcing Command Line Surveys – Get NPS Feedback from Developers(wootric.com)
9 points by prabhatjha 9y ago|0 comments
58.
How We Migrated from Heroku Postgres to AWS RDS(wootric.com)
16 points by prabhatjha 9y ago|0 comments
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by prabhatjha 9y ago
Hi -- Better is obviously relative so I can not say for sure without really trying their solution. I do know that most of these providers give you a generic classification like sports, entertainment, technology etc. That does not work for p
60.
A Look Under the Hood: AI for Customer Experience at Wootric(wootric.com)
18 points by prabhatjha 9y ago|3 comments

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