Deployment of Machine Learning Models

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Below are the top discussions from Reddit that mention this online Udemy course.

Learn how to integrate robust and reliable Machine Learning Pipelines in Production

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Taught by
Soledad Galli


Reddit Posts and Comments

0 posts • 12 mentions • top 10 shown below

r/datascience • comment
18 points • takuonline

My best resource was this course.

Its very good and will teach you you need to know from building machine learning pipelines (feature engineering + feature selection + model) through to deployment using docker +Circle ci + AwS/heroku.

It was an eye opener for me and l hope it helps you too.

r/datascience • comment
6 points • Strangeglove

Looks like, at the recommendd pace, AI Engineering seemed promising, and would be $100. Would probably pair with this guy next time it's on sale to get a taste of the prod life.

What's the verdict, r/ds - is the IBM cert course worth it?

r/learnmachinelearning • comment
1 points • BioGeek

r/datascience • comment
1 points • createAnAccount13

Udemy has a Machine Learning in Deployment course

r/datascience • comment
1 points • boy_named_su

there's a udemy course by a google lady:

i enjoyed her feature engineering course

r/datascience • comment
1 points • polandtown

really good course, took me a few weeks to get through. it might interest you.

r/datascience • comment
1 points • cleverfool11

I'd wait until it goes on sale, i got it for 10 bucks. Her other courses are good as well. She also had a feeture engineering, feature selection and testing and monitoring of ml models.

r/datascience • comment
1 points • PM_Me_Food_stuffs

r/MLQuestions • comment
2 points • daturkel

TrainInData offers some great courses focusing on ML in production. I still have a couple lessons from Testing and Monitoring ML Systems left, but I found it to be high quality material and well-explained. A coworker enjoyed their Deploying ML Models course.

Another good resource is company blogs. Not always strictly ML related, but:

all have high-quality tech blogs.

r/MLQuestions • comment
1 points • xepo3abp

What exactly do you mean by "cloud computing ML frameworks"?

The frameworks (tensorflow, keras, fastai) - are the same, local or cloud. I think what you're referring to is basically using cloud for ML.

If so there are 2 parts to it:

  1. Training
  2. Deployment / inference

Training is done the same locally or in the cloud, except for a few extra steps due to SSH. Here's a simple tutorial. If you want something more advanced, end to end, I know this dude does nice courses on AWS. They're a bit theoretical tho (like he's not a practitioner).

Mind that AWS also has an "autoML" solution called Sagemaker. Probably not what you want if you're a CS grad.

Deployment / inference - once you have your model you put it on a server and create an API. Here any tutorial to build a webserver should do + you simply upload your model with the rest of the code. I did this course on deploying ML at some point and enjoyed it. You could also look into serverless / lambda for ML deployment.

Alternatively to all this, if you just need to cheaply and quickly train your model check out It's a little side project that I built. We offer Tesla V100 instances at dirt-cheap prices ($0.99/hr for 1x Tesla). That's 1/3 of what you'd pay at GCP/AWS/paperspace!

If you get any questions, let me know! Happy to help!