Your Customers Are Changing, Your Data Should Too
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How data treated as "facts" degrades model accuracy and a proposed solution using event streams...
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5 steps to take as an antiracist data scientist
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Anti-racism work is personal, this article provides a unique lens for data scientists
Read MoreData + AI Lessons Learned from Covid-19
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Great talk on how data has changed since COVID-19—models are no longer predictive
Read MoreCommon problems taking ML from lab to production
A year ago
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A look into disappearing data and degraded performance preventing ML models from shipping
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My Love / Hate Relationship With Jupyter
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Why Jupyter delights Data Scientists and terrifies Machine Learning Engineers.
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Events
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Deep Learning Versus Machine Learning: What's the Difference?
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A contributed article by Charna Parkey in BuiltIn on thinking through which you should choose when applying data science to business problems
Read MoreThe state of machine learning: Why we need a new kind of datastore
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A contributed article by Davor Bonaci in DBTA on building systems for data scientist's needs like aggregations, historic data, and more
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