A little bit of each: data engineer and scientist, entrepreneur, physicist, writer and designer.
Ótimo artigo! Obrigado por liberar essa ferramenta para a comunidade. Vamos aprender a usar na EmCasa!
Didn’t think about that before. Will try to do it and update the article.
Sure, go ahead and translate it! I’ll be pleased to have my work translated!
Just mention me and insert a link to the original. Also send me the translated article’s link when you’re done!
Thanks for reading! Yes that data was available and was used as predictor. It is also one of the strongest features. You may check it out here: https://www.kaggle.com/andresionek/what-makes-a-kaggler-valuable
There is complementary data in the Kernel, but not everything that you mentioned. I would love to see how medium articles/social media influence salaries, but we don’t have this data.
Good point! I’ll make an edit, showing the intercept (location of zero) and how the coefficients affect it.