Linear regression is a basic predictive analytics technique that uses historical data to predict an output variable. It is popular for predictive m...
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Thank you so much for showing how to do it manually. There are so many articles showing different data analysis techniques, but a lot of them start off with:
This was sooooo nice to be able to sit through a nice, clear walkthrough of the math behind it with helpful graphs and visuals. It makes me so happy. Thanks again :)
I'm glad you enjoyed it! :) We'll be releasing a lot more tutorials in the upcoming months...is there anything in particular you'd like to learn?
Not specifically, but I would love to see more posts with more background on common data science algorithms and how they work.
There is one thing I would have liked to see:
When you provided this formula/definition I would have liked to read something like this:
"It is called linear regression because it is linear in its parameters β"
or so. My ML/DL professor mentioned it on every of his slides about linear regression. Therefore an equation like
f(x) = ∑ βi x2
would be linear too, because it is linear in its parameters (β)
Beside that I really like your explanations! Definitely would like to read more about advanced topics :)
That's a great point. Thank you :) more coming soon!
As a beginner, i think your post is really clear. Nice work, keep going!
Thanks! Glad you liked it :)