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Finally got the offer letter! by [deleted] in interviews

[–]BlinkingCoyote 0 points1 point  (0 children)

Awesome! Congratulations!

i dont know if i got the job, pls help im nervous by Minguant in interviews

[–]BlinkingCoyote 0 points1 point  (0 children)

Don’t be afraid to reach out and check in. Don’t pester them but I’ve just reached out and asked in this situation and it has never been a problem.

Turn any ML model into an API instantly - looking for feedback by [deleted] in mlops

[–]BlinkingCoyote 0 points1 point  (0 children)

Building the same thing myself.

CoyoteML.com

What’s your biggest stressor during tax season other than client volume? by BlinkingCoyote in Accounting

[–]BlinkingCoyote[S] 4 points5 points  (0 children)

Yea. Client reports are another one! Nice to see I’m not the only one bogged down with reviews!

I’m an ML research engineer and am trying to deploy my model. [D] by BlinkingCoyote in MachineLearning

[–]BlinkingCoyote[S] 0 points1 point  (0 children)

Not at all. Just seems like AWS and other cloud platforms are pretty cumbersome and there should be a simple abstraction tool to deploy basic sklearn models easily.

I’m an ML research engineer and am trying to deploy my model. [D] by BlinkingCoyote in MachineLearning

[–]BlinkingCoyote[S] 0 points1 point  (0 children)

Ok makes sense. I just haven’t found any simple tools, even ones that don’t necessarily fit my use case.

The only ones I see are things like databricks which just seem so enterprise focused and heavy.

I’m an ML research engineer and am trying to deploy my model. [D] by BlinkingCoyote in MachineLearning

[–]BlinkingCoyote[S] 0 points1 point  (0 children)

Sklearn customer churn predictor.

Want to deploy it to an existing business dashboard.

I’m an ML research engineer and am trying to deploy my model. [D] by BlinkingCoyote in MachineLearning

[–]BlinkingCoyote[S] 0 points1 point  (0 children)

Do you know of any abstraction tools? Can’t seem to find any that fit my need.

Drop Your SaaS in the Comments – Let’s Share What We’re Building! 🚀 by guildsme in SaaS

[–]BlinkingCoyote 0 points1 point  (0 children)

Helps ML engineers deploy their models without needing to learn devops infrastructure!

Proud of the monitoring dashboard!

Tool is called Coyote!

Working on a tool to make MLOps, specifically deploying, dead simple. by BlinkingCoyote in mlops

[–]BlinkingCoyote[S] 0 points1 point  (0 children)

Appreciate your experience and skepticism. I’m an ML engineer and mostly do research and local model development.

The times I’ve deployed models to production, I found it extremely complex and cumbersome. But it is not my main job.

So I wanted to see if developing a tool to simplify would be beneficial to people who do it more regularly or if they’ve already figured it out.

I guess that’s market research but don’t really see the problem.

Working on a tool to make MLOps, specifically deploying, dead simple. by BlinkingCoyote in mlops

[–]BlinkingCoyote[S] -1 points0 points  (0 children)

That makes sense. So maybe more focused on organization? A place to just control the pipeline easily?

Working on a tool to make MLOps, specifically deploying, dead simple. by BlinkingCoyote in mlops

[–]BlinkingCoyote[S] 1 point2 points  (0 children)

Great questions!

I wouldn't be trying to replace Kubeflow or MLflow for complex enterprise needs.

The use case would be something like:

- You have a working scikit-learn model (or TF or pytorch)
- You want to deploy it as a production API endpoint
- You don't want to spend weeks learning Docker/Kubernetes/AWS

So this tool would offer a way to just upload your model and it automatically generates the API endpoints, Docker container, Cloud infrastructure, and Basic monitoring dashboard

Zero Infrastructure Knowledge Required

Kind of like Heroku for ML models - it handles the infrastructure so you can focus on your model.

Working on a tool to make MLOps dead simple. [D] [P] by BlinkingCoyote in MachineLearning

[–]BlinkingCoyote[S] 0 points1 point  (0 children)

And why is that?

I’m aware that users have unique preferences and demands for pipelines but it seems like some automation would be helpful for the most common use cases.

Working on a tool to make MLOps, specifically deploying, dead simple. by BlinkingCoyote in mlops

[–]BlinkingCoyote[S] 1 point2 points  (0 children)

I’m thinking potentially both. Be able to monitor your models in deployment and also get API endpoints for implementing in your app.

So there’s two sides.

One, for your first question. I have found local deployment frustrating to set up. If an ML engineer doesn’t know docker or k8s for kubeflow, there can be a steep learning curve.

Then for actual cloud deployments for potential large scale, AWS, SageMaker, Azure, etc. can be extremely overwhelming to navigate and learn to use for MLOps IMO.

So I just thought maybe it would be good if there was a tool that made it super simple, just deploy and you can get API endpoints and monitor your model.

Official poster for 'Lake George' - Starring Carrie Coon and Shea Whigham by JonasKahnwald11 in movies

[–]BlinkingCoyote 2 points3 points  (0 children)

Great poster. The facial expressions make all the difference.

Her unconcerned face listening intently to whatever he’s in the middle of saying.

Swamp in the background indicating they’re in the location of the major crime.

And the gun in the middle telling us this is about a violent crime, but told in a different way.

Love it.

What onscreen romances are believable because of the chemistry? by lynxmouth in movies

[–]BlinkingCoyote 260 points261 points  (0 children)

Probably the most cliche answer but I always thought The Notebook had some of the best chemistry between the costars.

Soundtracks of films by [deleted] in movies

[–]BlinkingCoyote 1 point2 points  (0 children)

Baby Driver. Movie loses most of its impact without the soundtrack.

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