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Data Alchemy

38k members • Free

7 contributions to Data Alchemy
What is your current focus? ML / Datascience, LLMs or a mix of both?
I am curious to learn how others are approaching this. All the buzz is around LLM, but I feel that ML / Datascience is still quite relevant, but would like to hear your thoughts.
1 like • Apr '24
@Brandon Phillips That's actually super cool! Have you tried approaching business owners to check if they'd actually be interested in your solutions? I am juggling between the two (yeah, I know, not necessarily the best approach...). I'm trying to see which one I find more enjoyable
1 like • Apr '24
@Brandon Phillips Your last point is super true! "Data driven" is mostly a buzzword that people throw around to say that they have a dashboard. There is still a lot of value to be created with data, even in "data driven"organizations. may I ask your background? Do you have any experience in providing services in general, making business proposals, etc?
2 likes • Apr '24
@Marcio Pacheco I just updated the link! Valeu por avisar!
1 like • Apr '24
@Jeff Johnson I simply LOVE 3B1B, and cannot wait to see the sequences to this one!
Your wishlist of Python libraries to learn?
Anything non-standard (like Pandas or Numpy or other must-learns), but interesting and tempting? I have one on my list, but I'd like to know yours first :)
9 likes • Apr '24
Matplotlib, seaborn for dataviz! But these are quite standard. One that I found incredible and is supe easy to learn is CrewAI, to create AI agents crewAI. With it you can in literally 5 minutes have a working AI Agents script that does insane things... And with the tools capacity, the limit to their capacity is your imagination
Learn AI
It seems like the field of AI is very broad, I'm confused about what I should learn after learning Python?
6 likes • Mar '24
I would recommend that you go and do a project. No one "learns python", you learn the basics of Python, and then you familiarize yourself with a few libraries that will enable you to do more things. However, there are so many libraries out there that enable so many things that the best way is to decide on a project and try to do it! You will quickly realize that you need more tools to actually do the project, then you will research and find out about library X, and then Library Y, and so on... And of course you will find out about the different models, methods and techniques, and different ways to improve your results And this is actually **learning** AI! I highly recommend Kaggle: Your Machine Learning and Data Science Community to browse for project ideas with data easily available!
Everyone is recommending to learn statistics in depth
Whenever I ask seasoned data analysts (well... I asked three times in total), what is the most important thing to learn, I get the answer "statistics". Probability, regression, testing. And what would you say? Do you agree?
2 likes • Mar '24
In my opinion it reaaaally depends on what types of applications you want to build. If you are developing medical applications, that are highly regulated, complex and you cannot make mistakes, than sure, you probably need an advanced degree. However, several models work pretty well "out of the box" by just exploring the different techniques and with a basic understanding of statistics... If you want to go for this more general development, I don't think you need (at first) to go super deep into stats!
1-7 of 7
Vitor Tomaz
3
16points to level up
@vitor-tomaz-3725
I am Vitor, from Brazil. I am a project manager in management consulting, wanting to learn more about data science and AI.

Active 610d ago
Joined Dec 18, 2023
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