Data Skeptic
Data Skeptic
Kyle Polich
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.
Monetization of Youtube Conspiracy Theorists
Cameron Ballard joins us today to discuss his work around YouTube conspiracy theories. He revealed interesting observations about conspiracy theories on YouTube including how predatory ads are most common in conspiracy theory videos and how YouTube’s algorithm subtly works for predatory ads. Listen for more.
Aug 1
54 min
User Perceptions of Problematic Ads
Eric Zeng joins us to discuss his study around understanding bad ads and efforts that can be taken to limit bad ads online. He discussed how he and his co authors scrapped a large amount of ad data, applied a machine learning algorithm, and commensurate statistical results.
Jul 25
37 min
Political Digital Advertising Analysis
NaLette Brodnax, a political scientist and an Assistant Professor in the McCourt School of Public Policy at Georgetown University joins us to discuss her work on analyzing digital advertisements for political campaigns. She used data for electoral campaigns on Facebook to answer questions that help us better understand how digital ads affect the outcome of elections.   Click here for additional show notes! Thanks to our sponsor! https://neptune.ai/ Log, store, query, display, organize and compare all your model metadata in a single place
Jul 21
35 min
Privacy Preference Signals
Have you ever wondered what goes on under the hood when you accept a website’s cookies? Today, Maximilian Hils, a PhD student in Computer Science, at the University of Innsbruck, Austria, dissects the ad tech industry and the standards put in place to protect users’ data. He also shares his thoughts on the use of VPNs as well as other tools that help shield your data from prying eyes on the internet. Click here for additional show notes Thanks to our sponsor: https://clear.ml/ ClearML is an open-source MLOps solution users love to customize, helping you easily Track, Orchestrate, and Automate ML workflows at scale.
Jul 4
33 min
Neural Architecture Search for CTR Prediction
Ravi Krishna joins us today to talk about his recent work on a differentiable NAS framework for ads CTR prediction. He discussed what CTR prediction is about and why his NAS framework helps in building neural networks for better ads recommendation. Listen to learn about methodology, related literature and his results. Click for additional show notes Thanks to our sponsor: https://astrato.io Astrato is a modern BI and analytics platform built for the Snowflake Data Cloud. A next-generation live query data visualization and analytics solution, empowering everyone to make live data decisions.
Jun 27
28 min
Algorithmic PPC Management
Effectively managing a large budget of pay per click advertising demands software solutions. When spending multi-million dollar budgets on hundreds of thousands of keywords, an effective algorithmic strategy is required to optimize marketing objectives. In this episode, Nathan Janos joins us to share insights from his work in the ad tech industry. Click for additional show notes Thanks to our sponsor! https://wandb.com/ The developer-first MLOps platform. Build better models faster with experiment tracking, dataset versioning, and model management.
Jun 21
43 min
Data Skeptic: Ad Tech
Increasingly, people get most if not all of the information they consume online. Alongside the web sites, videos, apps, and other destinations, we’re consistently served advertisements alongside the organic content we search for or discover. Targetted ads make it possible for you to discover relevant new products you might otherwise not have heard about. Targetting can also open a pandora’s box of ethical considerations. Online advertising is a complex network of automated systems. Algorithms controlling algorithms controlling what we see. This season of Data Skeptic will focus on the applications of data science to digital advertising technology. In this first episode in particular, Kyle shares some of his own personal experiences and insights working in pay-per-click marketing. Click for additional show notes    
Jun 17
42 min
The Reliability of Mobile Phone Data
Our mobile phones generate an incredible amount of data inbound and outbound. In today’s episode, Nishant Kishore, a PhD graduate of Harvard University in Infectious Disease Epidemiology, explains how mobility data from mobile phones can be captured and analysed to understand the spread of infectious diseases. Click here for additional show notes Thanks to our sponsor! https://neptune.ai/ Log, store, query, display, organize, and compare all your model metadata in a single place
Jun 12
49 min
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