🔖 The Top 5 Papers About #mlops You Should Know (Part 1)

I've seen a ton of lists about the most important papers in #ml, #datascience, #deeplearning, #mlengineering.

But I've either seen not that many #mlops reading lists or when I do run across them they tend to be focused a bit too deeply on specific ML systems or domains or algorithms.

👉🏻 If you only read 5 papers to understand why ML is hard (and how big the problem space of MLOps is) it should be these papers.

[To Be Continued]

Does anyone here have experience with #Prefect? What's the best way to automate blocks? can you do it via #terraform? #ml #mlengineering

The tools we have today are better than the ones we had before and this is especially true in the #mlops world. We have more options than ever before (cc: MAD Turck Landscape) but confusion is just as high as it ever was.

#mlops #productionml #mlengineering #oss #devtools #python

Having #DataScientists Build Infrastructure & Developing Models At The Same Time Is A Terrible Anti-Pattern We’re Addicted To.

Esp at comps that aren’t early stage -- correlated w/ a lack of technical DS leadership, poor infra design, and lack of organizational alignment.

Really shows how the difference between success & failure isn’t technology choices but good project management & strategic leadership around platforms.

#mlops #mlengineering #mlplatforms #datascience

👉🏻 Online Inference =/= Streaming

We're all aware of this right? That they're not the same thing?

#mlops #mlengineering #datascience #dataengineering #productionml #mlsystems #systemdesign

🤔 Rather than trying to get rid of the #datascientist title, maybe we just treat it as an abstract class and continue on our merry ways?

#datascience #dataengineering #mlops #mlengineering #ai #career #data

RT @BazeleyMikiko
For folks now wondering why there are. SO. MANY. FEATURE. STORES, it's helpful to read @simba_khadder 's article to understadn the differences: https://www.featureform.com/post/feature-stores-explained-the-three-common-architectures

#datascience #mlops #mlengineering https://twitter.com/vboykis/status/1622410293308526592

🤔To bootcamp or not to bootcamp?

Like all annoying senior devs, my answer is going to be: "It depends".

I breakdown what consider when choosing the #bootcamp route for #datascience (but advice good for other bootcamps like #dataengineering #mlengineering, etc)

#🐘 https://t.co/sTiiwWOB7D

If the answer is similar to:
1️⃣ ASAP
2️⃣ Minimal
3️⃣ Divorced
4️⃣ We can't
5️⃣ Less than 5

Then your first step shouldn't be building an ML platform, it should be developing models or ML-drive product features using the simplest, tried & true patterns possible.

#mlops #mlplatform #datascience #mlengineering #platformengineering #dataengineering #ai #mlinproduction

there’s a lot of really cool stuff in #MLEngineering that amounts to “train another model”. like using #SHAP to automate feature selection (first you have to train a model though). or #ConceptSHAP where you train simple linear models on the output of each neural net layer. or anomaly detection, or autoencoders, or...

😳 My talk proposal to the #mlops track was accepted to #DataCouncilAustin2023 🤯

🎉 What an exciting way to start the year! 😃

Looking forward to connecting with folks in Austin from March 28-30th on #mlops #productionml #mlengineering #productiondatascience

Please feel free to connect with me on LI if you're attending or presenting!
https://www.linkedin.com/in/mikikobazeley/