Statistics history, interdisciplinarity, and data and society. Chris Wiggins talks with Jon Krohn about the power dynamics of data, the transformation of the field of biology through data-driven approaches to genetic sequencing, and the New York Times’ data science team’s cutting-edge approach to accommodating its tech stack.

This episode is brought to you by the AWS Insiders Podcast (https://pod.link/1608453414) and by Modelbit (https://modelbit.com), for deploying models in seconds. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• The importance of the humanities in data science [09:18]
• How data science “rearranges” power [17:19]
• An overview of How Data Happened [20:36]
• The controversial nature of Bayes theorem [29:16]
• Why we need to consider data ethics [34:00]
• How biology came to adopt data science into its field [45:44]
• The data science tech stack at the New York Times [49:18]

Additional materials: www.superdatascience.com/703

The Super Data Science Podcast: Machine Learning | AI | Success

703: How Data Happened: A History, with Columbia Prof. Chris Wiggins

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

703: How Data Happened: A History, with Columbia Prof. Chris Wiggins

Super Data Science: ML & AI Podcast with Jon Krohn