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Haha great idea! Should probably ask this to the next guest on this podcast 😅

Thanks you so much for you nice comment, you've made my day! It really means a lot to me! Very happy to hear that you enjoy the format of the podcast and that the content is accessible. We have some great episodes that will be released in the coming weeks, hope you'll enjoy :)

I think we must not see this literally as 1 and 2 and so on.. As far as I understood, what he meant was basically let's say there is a product for which a user provided a rating of 1, and for this, you can't predict how better the product must be for someone to give it a rating of 2 for it. Like there is distinction between the consequent ratings but there is no measurable distinction between those. He also quoted another example of predicting the damage caused to a house or a car like damaged, severely damaged. These don't have measurable distinctions.

Yes Sebastian is really inspiring! There is so much to learn from him and his career

It's our pleasure! Hope you enjoyed the conversation :)

Petar is indeed an amazing guest! Thanks a lot for the intro Louis :)

My pleasure! Hope you enjoyed the episode :)

Thanks a lot :)

Thanks a lot to you, very happy to hear that you learned from our conversation with Christof

Thanks a lot Phil :)

Thanks Louis, very glad that you subscribed and enjoyed the episode

Very happy to hear that you enjoyed the episode! Definitely a lot to learn from Lewis. Thanks for subscribing :)

Thanks a lot :) Happy to hear that you’ve enjoyed the episode

Thanks a lot Ahmed! Very happy to hear that you’re enjoying AI stories :)

The company is called NannyML: github.com/NannyML/nannyml

Thanks Jonathan, glad to hear that you’ve enjoyed the episode :)

Yes agree! Mike was an amazing and super inspiring guest

Thanks :)

Thanks a lot :) You can find Maxime's course here: github.com/mlabonne/llm-course and Lil'Log is also mentioned: And Lil'Log is also mentioned: lilianweng.github.io/. Is this what you were looking for?

Thanks a lot! Very happy to hear you enjoyed our conversation :) Hope this will be useful to you

Thanks a lot Jo!

It’s our pleasure Luciano! Thanks for your kind comment :)

Thanks a lot!! Very glad to hear that you enjoyed our conversation

Thanks a lot Phil :)

Thanks Nathan! There will be more to come 👌🚀

Yes Christoph is super inspiring! Definitely a lot to learn from him :)

Yes definitely agree! They're building a great product

Thanks so much! Very happy to hear that you’ve enjoyed the conversation :)

Thanks a lot! Glad to hear that you've enjoyed the episode :)

Glad to hear that you enjoyed the conversation :)

Thanks :)

Thanks a lot ! :)

That's amazing! Good luck with your AI/ML journey then 😊

Our pleasure! Glad to hear that your enjoyed the episode :)

Thanks a lot, very glad to hear that you enjoyed the conversation :)

*transition to ML

It’s true that the market is getting more and more competitive. But if you really want it, you can do it. Keep applying and keep progressing at the same time. Either by taking an analytics role and then transitioning into Data Science / Machine learning later on or by working on a side project or taking online courses. If you keep progressing and really want it, then you can do it!

@@aistoriespodcast The reality is more harsh than our interests. Define me wanting something, if one devotes his 5-10 years he will even complete another related bachelor and masters along with his own projects to qualify. Thats not justice when someone 2 3 years ago just enters the field with only a few data sciencew projects right? So what you say is not completely honest. Today its not even worth transitioning to this field if you are already on another field but it was 2 years ago... I hate it when youtubers and fake influencers try to market their transition made when its much easier than todays world. They dont know and dont care how harder it is than the past...

@@aistoriespodcast As I said on previous reply just be honest, if youre not really trying transitioning today, you dont know nothing on that.. The internet is full of lying marketing on data science and youre just fooling many people. Just give me statistics of what percent of people trying nowadays got a real job on this field?? (not data analytics jobs or internships that they work you on free and drop you off later..) I dont say its not possible for a fresher if you have a CS degree or maybe statistics BS.. People trying transtion (NOWADAYS!) are doomed I can honestly sayt that unlike you...

@@deniz.7200it is definitely not easy but if you really want it you can do it. Transitioning in the field can mean a lot of things and there are lots of ways to do it. For example, you can start working in a non-technical position at a tech company, learn on the side and transition slowly to a Data Science position.