Twitter | Search | |
Big Dragon Energy Mar 18
"Machine learning engineer" is just a name data scientists started calling themselves to feel different from all the up and coming data analytics people calling themselves data scientists.
Reply Retweet Like
Big Dragon Energy
This is made funnier by the fact that anyone with brains and an hour at Google can take an api and jam out a machine learning model. The hard part is businesses never have clean data in a usable format to attach these too so you are looking at 90% data cleaning 10% ML 2/3
Reply Retweet Like More
Actually, Mar 18
Replying to @forestsfailyou
Hard truths
Reply Retweet Like
Big Dragon Energy Mar 18
Replying to @forestsfailyou
Finally you have the fact that any doofus with an autoML/driverlessAI/aws machine learning account can make these with literally no effort.
Reply Retweet Like
Kojo Idrissa @ Home #NorAmGT Mar 18
Replying to @eaton @forestsfailyou
And THAT is LITERALLY the reason my talks on using Python w/ spreadsheets end w/, “But what if your data ISN’T well structured?” Cuz it’s not.
Reply Retweet Like
Actually, Mar 18
EVER
Reply Retweet Like
Big Dragon Energy Mar 18
Replying to @eaton @Transition
I saw a project once where they put data in the freaking Excel pop out comments and encoded data in the text of the colors. Took weeks to finally make Python execute VB code to extract it all.
Reply Retweet Like
Russell Jurney Mar 18
Replying to @forestsfailyou
Didn’t read it but it made me laugh because it rings true. Ppl have jumped off the data science raft and onto the AI boat and calling themselves machine learning engineers because they don’t (wanna) do ETL all day. How do you distinguish between a 15 year v 6 week data scientist?
Reply Retweet Like