Data Science Challenges
Tim and Keith discuss the challenges faced by data scientists, emphasizing the cultural differences between data science and software engineering. They highlight the importance of managing handshakes between different roles in the data science lifecycle and the significant amount of work that goes into data engineering and cleansing. Keith warns about the pitfalls of look ahead bias during the research phase, which can lead to setbacks in model development.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Programming Languages, Software Engineering and Machine Learning
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