Early last year, I wanted to learn about Machine Learning Operations(MLOps).

MLOps refers to the whole processes involved in building and deploying machine learning models reliably.

A thread on the importance of MLOps and resources that I used 🧵

As you may have heard, models are a tiny part of any typical ML-powered application.

There is nothing that stresses that as this picture:

Source: Hidden Technical Debt in Machine Learning Systems, https://t.co/JDyAr1s3kc
There are lots of critical processes that are involved in MLOps such as:

- Data processes: collection, labeling, exploration, preprocessing
- Modeling processes: building, training, evaluation, testing
- Production processes - Serving, monitoring, and maintaining models
MLOps is a new topic for almost anyone. Maintaining models for a prolonged period of time is difficult.

Models are very prone to change. They drift over time. The world (that sources the data) changes, and so data change too.
MLOps is a huge topic. All I wanted was to have a reasonable understanding of it.

Here are 3 resources that I used:

- Machine Learning Engineering book by @burkov
- MLOps Specialization by @DeepLearningAI_
- Introducing MLOps book Oreilly
Here are links for those resources:

- ML Engineering book: https://t.co/L5trxHGAw1
- Introducing MLOps: https://t.co/de4vxdzA5P
- MLOps specialization: https://t.co/46fhFSyEno
I also wrote a couple of blog posts as I was learning it. You can find the blogposts on Medium

https://t.co/DFp6LwqxRV
If you would like to get started with MLOps, I recommend you take MLOps specialization along with one of those books, preferably ML Engineering book.
Also, @MadeWithML by @GokuMohandas contains many hands-on resources for building and productionizing machine learning models.

I can't recommend it enough too!

https://t.co/WjYQpeXcTX
If you have mainly been building models, learning MLOps might be the next good step for you. It's a useful skill to have!
Thanks for reading!

If you would like to see more machine learning content and useful resources, follow me at @Jeande_d.

You can also share the thread with others if you found it helpful. Sharing is caring :)

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Ivor Cummins has been wrong (or lying) almost entirely throughout this pandemic and got paid handsomly for it.

He has been wrong (or lying) so often that it will be nearly impossible for me to track every grift, lie, deceit, manipulation he has pulled. I will use...


... other sources who have been trying to shine on light on this grifter (as I have tried to do, time and again:


Example #1: "Still not seeing Sweden signal versus Denmark really"... There it was (Images attached).
19 to 80 is an over 300% difference.

Tweet: https://t.co/36FnYnsRT9


Example #2 - "Yes, I'm comparing the Noridcs / No, you cannot compare the Nordics."

I wonder why...

Tweets: https://t.co/XLfoX4rpck / https://t.co/vjE1ctLU5x


Example #3 - "I'm only looking at what makes the data fit in my favour" a.k.a moving the goalposts.

Tweets: https://t.co/vcDpTu3qyj / https://t.co/CA3N6hC2Lq

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