Machine Learning has been around for years, what does it look like today? Carl and Richard chat with Zoiner Tejada about how he approaches machine learning today, starting with a focus on data. The bulk of the work for using machine learning is focused on sources, quality and bias in data. Zoiner talks about using data lakes to organize data simply, and be able to filter it for processing quickly. Often, it makes sense to duplicate data for processing efficiency! The conversation then dives into the role of algorithms, training and testing, and what it means to be a data scientist.

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