Every hypothesis must earn the right to be believed.
That means:
• Testing it statistically
• Validating it with data
• Challenging it against evidence
• Allowing the numbers to speak before conclusions are made
A beautiful dashboard with weak analysis is still weak!
“The letters after his name don’t mean a thing without the evidence to back up his position.” — Norm Geisler
One of the biggest disasters in data analysis is ...
assumption.
Assumption quietly kills objectivity.
It squeezes the integrity out of recommendations long before the final report is presented.
In data analysis, confidence is not competence.
Titles are not proof.
Gut feelings are not insights.
Everyone keeps saying "learn machine learning" but nobody tells you where to actually begin.
We're fixing that.
Our guest, Mr. Joseph Elijah @Joseph_Joey541 (AI/ML Engineer at SMART AI Consult), is bringing real answers to the questions you've been asking.
Join the conversation at 8PM, tomorrow, here - https://t.co/pc3loJlnza
Tag a friend/machine learning enthusiast who needs to see this.
@Elishaokon01 Hello El'
I listened to your podcast.
My question:
"Is there a chance that democracy will go extinct in some 100 to 200 years from now, just like the monarchy system is already eroding?