Regional Differences in Data Science
Buck Woody discusses how data science practices vary across regions, highlighting differences in preparation and platforms. He also emphasizes the importance of understanding the programming languages and tools preferred in different regions. Additionally, he mentions the significance of familiarizing oneself with Kubernetes and containers in the data science field.In this clip
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