Data Driven Babe

A bootcamp by @goabiaryan | Making learning MLOps more fun for everyone | #ML #DataOps #MLOps

[Data Driven Babe @datadrivenbabe]

What is your preferred way of learning new technologies?

[Andrej Karpathy @karpathy]

RE: "how often do you see teams actually fine tuning LLMs?"
It's an interesting question, about how prompting (optimization over prefix tokens) and finetuning (optimization over weights) will be used over time. If people have data points please pitch in.
I expect that finetuning is still quite new / a lot more involved (accessible data collection, optimization, expertise around making it work) but a lot of this is improving.

[Abi Aryan @GoAbiAryan]

In 2023, Data Engineering is the fastest-growing field in machine learning. A lot of challenges that we have previously explored in database design are now being adapted to Machine Learning.

Here are some of my fav papers on the topic: 👇🧵

[Khuram Zaman @zamandigital]

This course overview with @GoAbiAryan is pretty dope! It feels like all my data engineering / MLOps questions are addressed in one place.

👇Topics covered 👇

[Abi Aryan @GoAbiAryan]

What to do about LLM FOMO?

Learn to be a tester.

When done with testing, get back to the fundamentals-
1. Customer acquisition
2. Database management
3. Putting models in production
4. Personalization
5. Making revenue

Don't get attached to tools, use tools to ur own end!

[Abi Aryan @GoAbiAryan]

My *slightly* contrarian take is that our decision processes emulate probabilistic causal reasoning far more than deterministic causal reasoning. And if so, the LLMs are likely a step in the right direction when it comes to general intelligence and developing performant systems.

[Abi Aryan @GoAbiAryan]

3 days ago, I picked up the book Fluent Python and as I am going through it, I am surprised I didn't pick it earlier.

Cannot recommend enough.

[Abi Aryan @GoAbiAryan]

What got you interested in MLOps?

[Data Driven Babe @datadrivenbabe]

@datawithsuman @SaveToNotion #thread

[Aurimas Griciūnas @Aurimas_Gr]

There is a lot that has to be covered from a #DataEngineering perspective before a company can consider implementing some of the #MLOps practices.

Invest unproportionally large amounts into your #DataEngineering efforts.

[Abi Aryan @GoAbiAryan]

If you liked the conversation, you're certainly going to love @AiSimonThompson's new book on the topic that we talk about extensively on the podcast outro https://t.co/aNN0bZVcch

[Data Driven Babe @datadrivenbabe]

@GoAbiAryan @AiSimonThompson @SaveToNotion #thread #MLOps

[Abi Aryan @GoAbiAryan]

Two weeks ago, I got to ask Simon @AiSimonThompson some pressing questions about managing machine learning projects.

Here are some of my fav takeaways from that conversation. A thread 🧵⤵️

[Abi Aryan @GoAbiAryan]

This has been such an excellent year for software system design in ML. So, I compiled a list of some of my favorite papers 📜in MLOps.

Here are some of my favorite ones till date⤵️

[Data Driven Babe @datadrivenbabe]

@SeattleDataGuy Love it esp 3.

[Abi Aryan @GoAbiAryan]

Jason is giving out 3 copies of MadewithTFJS book, grab yours now 🧑‍🏫

[Data Driven Babe @datadrivenbabe]

Coming in May: DataEngineering Ecosystem

When? May 30th, 2021 ⏲️

More details to be announced soon 🎉🎋

[Data Driven Babe @datadrivenbabe]

We have three events coming up for May, June, and July. To pick the next session, we're opening it to a vote - which one do you want next?

[Data Driven Babe @datadrivenbabe]

In Data Engineering EcoSystems, we will discuss the data engineering processes for full-stack applications briefly touching on data science processing pipelines, ML models, pipeline management tools, databases, front-end and more.

[Data Driven Babe @datadrivenbabe]

We have three events coming up for May, June, and July. To pick the next session, we're opening it to a vote - which one do you want next?

[Data Driven Babe @datadrivenbabe]

- A Noob's Intro to Python helps you develop an intuitive understanding of programming concepts and Python syntax.

- Designing Data-Intensive Scalable Apps will be focused on system design for building scalable and reliable applications with online services and modern databases.