DataTalks.Club

Links:

• Twitter: https://twitter.com/dead_flowers22
• LinkedIn: https://www.linkedin.com/in/roksolanadiachuk/

Join DataTalks.Club: https://datatalks.club/slack.html

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We talked about:

• Meryam's background
• The constant evolution of startups
• How Meryam became interested in LLMs
• What is an LLM (generative vs non-generative models)?
• Why LLMs are important
• Open source models vs API models
• What TitanML does
• How fine-tuning a model helps in LLM use cases
• Fine-tuning generative models
• How generative models change the landscape of human work
• How to adjust models over time
• Vector databases and LLMs
• How to choose an open source LLM or an API
• Measuring input data quality
• Meryam's resource recommendations

Links:

• Website: https://www.titanml.co/
• Beta docs: https://titanml.gitbook.io/iris-documentation/overview/guide-to-titanml...
• Using llama2.0 in TitanML Blog: https://medium.com/@TitanML/the-easiest-way-to-fine-tune-and-inference-llama-2-0-8d8900a57d57
• Discord: https://discord.gg/83RmHTjZgf
• Meryem LinkedIn: https://www.linkedin.com/in/meryemarik/

Free MLOps course: https://github.com/DataTalksClub/mlops-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

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hi everyone Welcome to our event this event is brought to you by data dos club which is a community of people who love

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data and we have weekly events and today one is one of such events and I guess we

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are also a community of people who like to wake up early if you're from the states right Christopher or maybe not so

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much because this is the time we usually have uh uh our events uh for our guests

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and presenters from the states we usually do it in the evening of Berlin time but yes unfortunately it kind of

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slipped my mind but anyways we have a lot of events you can check them in the

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description like there's a link um I don't think there are a lot of them right now on that link but we will be

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adding more and more I think we have like five or six uh interviews scheduled so um keep an eye on that do not forget

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to subscribe to our YouTube channel this way you will get notified about all our future streams that will be as awesome

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as the one today and of course very important do not forget to join our community where you can hang out with

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other data enthusiasts during today's interview you can ask any question there's a pin Link in live chat so click

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on that link ask your question and we will be covering these questions during the interview now I will stop sharing my

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screen and uh there is there's a a message in uh and Christopher is from

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you so we actually have this on YouTube but so they have not seen what you wrote

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but there is a message from to anyone who's watching this right now from Christopher saying hello everyone can I

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call you Chris or you okay I should go I should uh I should look on YouTube then okay yeah but anyways I'll you don't

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need like you we'll need to focus on answering questions and I'll keep an eye

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I'll be keeping an eye on all the question questions so um

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yeah if you're ready we can start I'm ready yeah and you prefer Christopher

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not Chris right Chris is fine Chris is fine it's a bit shorter um

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okay so this week we'll talk about data Ops again maybe it's a tradition that we talk about data Ops every like once per

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year but we actually skipped one year so because we did not have we haven't had

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Chris for some time so today we have a very special guest Christopher Christopher is the co-founder CEO and

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head chef or hat cook at data kitchen with 25 years of experience maybe this

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is outdated uh cuz probably now you have more and maybe you stopped counting I

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don't know but like with tons of years of experience in analytics and software engineering Christopher is known as the

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co-author of the data Ops cookbook and data Ops Manifesto and it's not the

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first time we have Christopher here on the podcast we interviewed him two years ago also about data Ops and this one

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will be about data hops so we'll catch up and see what actually changed in in

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these two years and yeah so welcome to the interview well thank you for having

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me I'm I'm happy to be here and talking all things related to data Ops and why

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why why bother with data Ops and happy to talk about the company or or what's changed

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excited yeah so let's dive in so the questions for today's interview are prepared by Johanna berer as always

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thanks Johanna for your help so before we start with our main topic for today

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data Ops uh let's start with your ground can you tell us about your career Journey so far and also for those who

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have not heard have not listened to the previous podcast maybe you can um talk

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about yourself and also for those who did listen to the previous you can also maybe give a summary of what has changed

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in the last two years so we'll do yeah so um my name is Chris so I guess I'm

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a sort of an engineer so I spent about the first 15 years of my career in

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software sort of working and building some AI systems some non- AI systems uh

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at uh Us's NASA and MIT linol lab and then some startups and then um

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Microsoft and then about 2005 I got I got the data bug uh I think you know my

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kids were small and I thought oh this data thing was easy and I'd be able to go home uh for dinner at 5 and life

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would be fine um because I was a big you started your own company right and uh it didn't work out that way

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and um a...

We talked about:

• Ivan’s background
• How Ivan became interested in investing
• Getting financial data to run simulations
• Open, High, Low, Close, Volume
• Risk management strategy
• Testing your trading strategies
• Sticking to your strategy
• Important metrics and remembering about trading fees
• Important features
• Deployment
• How DataTalks.Club courses helped Ivan
• Ivan’s site and course sign-up

Links:

• Exploring Finance APIs: https://pythoninvest.com/long-read/exploring-finance-apis
• Python Invest Blog Articles: https://pythoninvest.com/blog

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Links:

• Biodiversity and Artificial Intelligence pdf: https://www.gpai.ai/projects/responsible-ai/environment/biodiversity-and-AI-opportunities-recommendations-for-action.pdf

Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html