393: The Importance of Keeping Science in Data Science
John Peach joins to discuss his passion for bringing more scientific approaches to the data science field, making it smarter and more efficient.
In this episode you will learn:
John’s move from Canada to the US [3:37]
John’s new position at Oracle [8:31]
Data Science Workflows [9:34]
John’s solution to data science workflow exploration [12:06]
John’s data science design thinking framework [21:20]
Case study [34:21]
Literate statistical programming [43:12]
R or Python? [51:55]
Data unit testing [53:28]
What drives John? [1:00:56]
Additional materials: www.superdatascience.com/393
Om Podcasten
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.