Banana Data Podcast

Welcome back to our bi-weekly episodes of Season 5 of the Banana Data Podcast! This season, we’re ushering in the notion of humanizing data science. In last week’s episode, we explored the importance of storytelling with data. This week, we discuss data visualization with Nathan Mannheimer, Director of Data Science and Machine Learning at Tableau. Subscribe to the Banana Data Podcast on Apple or Spotify to receive alerts and stay up to date on the big conversation in data and AI.
Check out what we've been reading:

• Humanizing AI: A Case For Cognitive Design Thinking And Custom AI
• Human-Looking Data Visualizations Don’t Boost Empathy — Yet

Be sure to subscribe to our weekly newsletter to get this podcast & a host of new and exciting data-happenings in your inbox!

Welcome back to our bi-weekly episodes of Season 5 of the Banana Data Podcast! This season, we’re ushering in the notion of humanizing data science. In last week’s episode, we explored the importance of human in the loop within the ML pipeline with Christina Hsiao, Senior Product Marketing Manager at Dataiku. This week, we discuss storytelling with data. Subscribe to the Banana Data Podcast on Apple or Spotify to receive alerts and stay up to date on the big conversation in data and AI.
Check out what we've been reading and watching:

• Using Visualization to share the human impact of Numbers
• The Power in Effective Data Storytelling
• Making Data Mean More Through Storytelling

Be sure to subscribe to our weekly newsletter to get this podcast & a host of new and exciting data-happenings in your inbox!

Welcome back to our bi-weekly episodes of Season 5 of the Banana Data Podcast! This season, we’re ushering in the notion of humanizing data science. In last week’s episode, we discussed what happens when humanization fails and consequences that can occur with Jeremie Harris Towards Data Science. This week, we are joined by Christina Hsiao, Senior Product Manager at Dataiku to discuss the importance of having a human in the loop within the ML pipeline. Subscribe to the Banana Data Podcast on Apple or Spotify to receive alerts and stay up to date on the big conversation in data and AI.
Check out what we've been reading:

• What's MLOps? Managing complex ML systems at Scale
• MLOps as a Critical, Emerging Role

Be sure to subscribe to our weekly newsletter to get this podcast & a host of new and exciting data-happenings in your inbox!

Welcome back to our bi-weekly episodes of Season 5 of the Banana Data Podcast! This season, we’re ushering in the notion of humanizing data science. In last week’s episode, we discussed differing methodologies and functionalities within the data science field with Emma Irwin, Solutions Engineer at Dataiku. This week, we are joined by Jeremie Harris of Towards Data Science to discuss what happens when humanization fails and consequences that can occur. Subscribe to the Banana Data Podcast on Apple or Spotify to receive alerts and stay up to date on the big conversation in data and AI.
Check out what we've been reading and watching:

• Becoming an Intelligent Organization in the Age of AI: Firsthand Strategies From the CDO of Morgan Stanley
• Artificial Intelligence and Ethics: Sixteen Challenges and Opportunities

Be sure to subscribe to our weekly newsletter to get this podcast & a host of new and exciting data-happenings in your inbox!

On episode two of the podcast, Triveni and Will look at how digital assistants may perpetuate biased data, how multi-armed bandits can build a top-notch recommendation system (and win over Triveni’s heart), and their interview with Mark Buckler, PhD candidate at Cornell and author of the article, “How to Make Bad Deep Learning Hardware” on why understanding hardware may be the key to building your best models yet.

Learn more about the articles referenced in this episode below:
How Digital Virtual Assistants Like Alexa Amplify Sexism by Morgan Meaker (OneZero)
The Data Nutrition Project by Kasia Chmielinski and Sara Newman
Invisible Women: Data Bias in a World Designed for Men by Caroline Criado-Perez
Your Client Engagement Program Isn’t Doing What You Think It Is by Patric Glynn and Divya Prabhakar (Stichfix)
How to Make Bad Deep Learning Hardware by Mark Buckler (Cornell)