Data Science Skills
Keith reflects on the often-cited necessity of advanced math skills for data scientists, sharing his personal struggles with linear algebra. He questions the relevance of this model when applied to smaller organizations, emphasizing that understanding algorithms' history may be sufficient for practical applications. The discussion highlights the vast scale of data processing at major tech companies and contrasts it with the needs of regional businesses.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
655: AI ROI: How to get a profitable return on an AI-project investment — with Keith McCormick
Related Questions