r/askdatascience

New moderators needed - comment on this post to volunteer to become a moderator of this community.
▲ 3.1k r/askdatascience+423 crossposts

New moderators needed - comment on this post to volunteer to become a moderator of this community.

Hello everyone - this community is in need of a few new mods, and you can use the comments on this post to let us know why you’d like to be a mod here. 

Priority is given to redditors who have past activity in this community or other communities with related topics. It’s okay if you don’t have previous mod experience and our goal, when possible, is to add a group of moderators so you can work together to build the community.

Please use at least 3 sentences to explain why you’d like to be a mod and share what moderation experience you have (if any).  

If you are interested in learning more about being a moderator on Reddit, please visit redditforcommunity.com. This guide to joining a mod team is a helpful resource. 

Comments from those making repeated asks to adopt communities or that are off topic will be removed. 

u/GaryNOVA — 7 days ago
▲ 7 r/askdatascience+1 crossposts

Forecasting with AI?

How are you guys making decisions about how much discount to put on products, how do you plan supply / item velocity, how do you decide about your marketing spend and mix?

At my previous employer we had data scientists for this, now that I started my own business I don’t have this. I tried to ask claude, but the answers just look made up.

In the day and age of AI being everywhere there must be a way to do what a data scientist does without hiring data scientist right?

EDIT: on r/askdatascience someone recommended a tool called Qombra, looks like what I was l looking for, trying that now...

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u/ImAPilot02 — 9 days ago
▲ 4 r/askdatascience+1 crossposts

How do you guys do EDA when there are a lot of features?

I’ve been working on an ML project and this is my first time dealing with a dataset with a lot of features (around 60).

I’m kinda stuck on how to approach the EDA. With smaller datasets, I usually check the features one by one, look at distributions, missing values, outliers, relationships, etc. But with 50–60 features, I’m finding it really difficult to figure out what to focus on and what I can skip.

Do you guys actually do EDA on every feature, or is there some better way to approach this?

Would love to know how you handle this when working on real ML projects.

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u/avinsio — 9 days ago