機器學習工程師常見的錯誤操作_陳在民
Data engineering might be considered easy since there are many framework packages ready. However, it is really terrible for those engineers who don't really understand their data manipulations might not be valid in the end of putting into practices. Therefore, I gave an open discussion over the common mistakes. Instead of giving my answers, I chose to let AI engineers to vote whether the manipulations are valid. The simple results are also shown in the slides.
