Exploring No-Code Machine Learning, Database Efficiency, and Collaboration in Data Science

Einblick co-founder and associate professor at MIT, Tim Kraska, joins Jon Krohn to discuss no-code collaboration tools for data science and uncovers the clever database and machine learning tricks under the hood of the visual data computing platform.

In this episode you will learn:

• The inspiration behind Einblick [2:45]
• Einblick's progressive approximation engine [6:43]
• How no-code tools impact productivity [17:18]
• The critical steps to become more data-driven as an organization [24:30]
• How research universities like MIT support high-risk, long-term research [38:37]
• How ML applied to databases enables them to be faster and more efficient [42:03]
• How real-time collaboration environments like Google Docs are likely to become more widespread for data science tasks [ 49:24]

Additional materials: www.superdatascience.com/571