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Artwork for Data Skeptic

Data Skeptic

Kyle Polich
Large Language Models
Artificial Intelligence
Machine Learning
Generative AI
Github Copilot
Natural Language Processing
Avanade
C. Elegans
Data Science
Programming
Usability Research
AI In Software Development
Oil and Gas Industry
Microsoft
Artificial General Intelligence
HCI (human-Computer Interaction)
Survey Methodology
AI Ethics
Ethical AI
Productivity Gains

The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.

PublishesTwice monthlyEpisodes587Founded11 years ago
Number of ListenersCategories
TechnologyScienceMathematics

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Artwork for Data Skeptic

Latest Episodes

In this episode, Rebecca Salganik, a PhD student at the University of Rochester with a background in vocal performance and composition, discusses her research on fairness in music recommendation systems. She explores three key types of fairness—group... more

In this episode, we speak with Ashmi Banerjee, a doctoral candidate at the Technical University of Munich, about her pioneering research on AI-powered recommender systems in tourism. Ashmi illuminates how these systems can address exposure bias while... more

In this episode of Data Skeptic's Recommender Systems series, host Kyle Polich interviews Dr. Kunal Mukherjee, a postdoctoral research associate at Virginia Tech, about the paper "Z-REx: Human-Interpretable GNN Explanations for Real Estate Recommenda... more

Key Facts

Accepts Guests
Accepts Sponsors
Contact Information
Podcast Host
Number of Listeners
Find out how many people listen to this podcast per episode and each month.

Recent Guests

Ashmi Banerjee
Doctoral candidate at Technical University of Munich specializing in recommender systems and sustainable tourism.
Technical University of Munich
Episode: Sustainable Recommender Systems for Tourism
Kunal Mukherjee
Postdoctoral research associate at Virginia Tech focusing on graph-based intrusion detection and explanations in AI recommendations.
Virginia Tech
Episode: Interpretable Real Estate Recommendations
Sabrina Guidotti
Master student in computer science at the University of Milano, Bicocca
University of Milano, Bicocca
Episode: Why Am I Seeing This?
Dimitri Ognibene
Director of the Bicone Club at the University of Milano, Bicocca
University of Milano, Bicocca
Episode: Why Am I Seeing This?
Antonio Purificato
A second-year PhD student focused on recommender systems and environmental impacts of deep learning.
University of La Sapienza, Rome; Amazon Research
Episode: Eco-aware GNN Recommenders
Pål Grønås Drange
Associate Professor at the University of Bergen in the Department of Informatics
University of Bergen
Episode: The Network Diversion Problem
Baruch Barzel
Professor of Mathematics and Physics at Bar-Ilan University in Israel.
Bar-Ilan University
Episode: Complex Dynamic in Networks
Gabriel Ramirez
Manager for the notifications team at GitHub
GitHub
Episode: Github Network Analysis
Armin Pournaki
Joint PhD candidate at the Max Planck Institute for Mathematics and Sciences and Laboratoire Lattice and the Sciences Pour Media Lab in Paris.
Max Planck Institute for Mathematics and Sciences
Episode: Actantial Networks

Host

Kyle Politz
Host and primary interviewer, known for his comprehensive understanding of data science and machine learning topics.

Reviews

4.6 out of 5 stars from 1k ratings
  • A gem of a podcast

    I am not a data scientist, but I very much enjoy the podcast! It is fascinating, the interviewer’s really know their field and it has provided me with topics that could be interesting to follow-up. If you are interested in technology, or a student, then this is a podcast that is well worth following and listening to. Top marks!

    Apple Podcasts
    5
    AH24Z
    United Kingdom6 months ago
  • great

    great

    Apple Podcasts
    4
    JVo12
    Canada2 years ago
  • Nice podcast

    Listen it to learn industry English and new technology . Really good for me

    Apple Podcasts
    5
    jiazhi chao
    China2 years ago
  • Great resource

    A colleague introduced me to Data Skeptic last year and I’ve been enjoying the episodes. Kyle’s good at covering topics from many levels of data science understanding—his mini series with a non-data scientist are a great way to learn the basics!

    Apple Podcasts
    5
    calzone.onsets
    United States2 years ago
  • Data science

    Lots of interviews

    Apple Podcasts
    5
    joey...1989
    United States3 years ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

The podcast is seen as a great resource for both beginners and advanced listeners interested in data science and AI.
Some critique the audio quality and specific dynamics between the host and co-hosts, suggesting potential areas for improvement.
Listeners appreciate the depth of analysis and the quality of guests, remarking positively on the engaging discussions.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#177
United States/Technology
Apple Podcasts
#98
United Kingdom/Technology
Apple Podcasts
#189
Canada/Technology
Apple Podcasts
#176
Australia/Technology
Apple Podcasts
#185
France/Technology
Apple Podcasts
#200
Italy/Technology

Talking Points

Recent interactions between the hosts and their guests.

Sustainable Recommender Systems for Tourism
Q: What are the options?
Ashmi mentioned that the dataset and knowledge base are available on Hugging Face, being open source for public use.
Sustainable Recommender Systems for Tourism
Q: Could you give us like a formal definition of what you were looking into? What is exposure bias?
Exposure bias is defined as a combination of popularity bias and position bias, which affects how establishments are ranked on platforms.
Sustainable Recommender Systems for Tourism
Q: What first got you interested in recommender systems?
Ashmi shared that she got into recommender systems through her work with tourism data during her time at the Max Planck Institute.
Interpretable Real Estate Recommendations
Q: Can you give me some background on how you got involved in the project?
I got involved after observing the changes in the real estate market post-COVID and recognizing the need for users to have better recommendations, including emerging neighborhoods.
Eco-aware GNN Recommenders
Q: Could you describe Code Carbon and how you used it in the work?
Code Carbon is a framework to track CO2 equivalent emissions during model training, providing insights into energy consumption based on regional parameters and hardware specifications.

Audience Metrics

Listeners, social reach, demographics and more for this podcast.

Listeners per Episode
Gender Skew
Location
Interests
Professions
Age Range
Household Income
Social Media Reach

Frequently Asked Questions About Data Skeptic

What is Data Skeptic about and what kind of topics does it cover?

Focusing on the intersection of data science, machine learning, and critical thinking, listeners encounter a mix of insightful interviews and discussions with experts across various fields. The content frequently revolves around complex topics such as recommender systems, network analysis, and the implications of AI, making it an essential resource for those keen on uncovering the intricacies and challenges of these subjects. Notably, the show emphasizes not only the technical aspects but also the societal implications of data-driven technologies, fostering a deeper understanding of how they shape our world.

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How many episodes of Data Skeptic are there?

Data Skeptic launched 11 years ago and published 587 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

How do I contact Data Skeptic?

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What guests have appeared on Data Skeptic?

Recent guests on Data Skeptic include:

1. Ashmi Banerjee
2. Kunal Mukherjee
3. Sabrina Guidotti
4. Dimitri Ognibene
5. Antonio Purificato
6. Pål Grønås Drange
7. Baruch Barzel
8. Gabriel Ramirez

To view more recent guests and their details, simply upgrade your Rephonic account. You'll also get access to a typical guest profile to help you decide if the show is worth pitching.

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